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<title>Yan Lin's Presentations</title>
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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8">
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<title>Yan Lin's Presentations</title>
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<meta name="description" content="Yan Lin's Homepage, a collection of my publications, projects, and more.">
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<a class="link-secondary header-icon mx-2 py-0 my-0 h4 d-flex align-items-center" href="/" aria-label="Go to homepage">
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<svg xmlns="http://www.w3.org/2000/svg" width="1em" height="1em" fill="currentColor" class="bi bi-house-fill" viewBox="0 0 16 16" aria-hidden="true">
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<div class="col-8 text-center">
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<div class="page-header-logo h2 m-0" style="font-family: Impact, 'Arial Black', 'Franklin Gothic Bold', sans-serif;">Yan Lin's Presentations</div>
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</div>
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Guest lecture<span class='text-muted'> | </span>Aalborg University
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</p>
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<div class="d-flex gap-2">
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<a class="link icon-link icon-link-hover paper-link link-secondary" href="/assets/Self-supervised Learning of Trajectory Data.pdf" target="_blank" rel="noopener noreferrer">Slides</a>
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||||||
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||||||
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</div>
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||||||
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</div>
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||||||
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<h5 class="mb-1 paper-title">Self-supervised Learning of Trajectory Data</h5>
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</div>
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||||||
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||||||
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<div class="list-group-item px-0">
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<p class="d-inline-block mb-0 venue-name primary-text">
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Workshop presentation<span class='text-muted'> | </span>KDD 2024
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<a class="link icon-link icon-link-hover paper-link link-secondary" href="/assets/KDD_2024_Workshop_PLM4Traj.pdf" target="_blank" rel="noopener noreferrer">Slides</a>
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||||||
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||||||
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<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://arxiv.org/abs/2405.12459" target="_blank" rel="noopener noreferrer">Paper</a>
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||||||
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||||||
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</div>
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||||||
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</div>
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<h5 class="mb-1 paper-title">PLM4Traj: Leveraging Pre-trained Language Models for Cognizing Movement Patterns and Travel Purposes from Trajectories</h5>
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</div>
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||||||
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<div class="list-group-item px-0">
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<p class="d-inline-block mb-0 venue-name primary-text">
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Paper Oral<span class='text-muted'> | </span>SIGMOD 2024
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<div class="d-flex gap-2">
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<a class="link icon-link icon-link-hover paper-link link-secondary" href="/assets/SIGMOD-Oral-PPT.pdf" target="_blank" rel="noopener noreferrer">Slides</a>
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||||||
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||||||
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</div>
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||||||
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</div>
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||||||
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<h5 class="mb-1 paper-title">Origin-Destination Travel Time Oracle for Map-based Services</h5>
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</div>
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||||||
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||||||
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<div class="list-group-item px-0">
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||||||
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<div class="d-flex justify-content-between align-items-center mb-1">
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||||||
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<p class="d-inline-block mb-0 venue-name primary-text">
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Tutorial<span class='text-muted'> | </span>SpatialDI 2024
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</p>
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<div class="d-flex gap-2">
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||||||
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<a class="link icon-link icon-link-hover paper-link link-secondary" href="/assets/Talk on SpatialDI 2024.pdf" target="_blank" rel="noopener noreferrer">Slides</a>
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||||||
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</div>
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||||||
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</div>
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||||||
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<h5 class="mb-1 paper-title">Self-supervised Learning of Spatial-temporal Trajectories</h5>
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</div>
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<div class="list-group-item px-0">
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<div class="d-flex justify-content-between align-items-center mb-1">
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<p class="d-inline-block mb-0 venue-name primary-text">
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Paper Oral<span class='text-muted'> | </span>AAAI 2021
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</p>
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<div class="d-flex gap-2">
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<a class="link icon-link icon-link-hover paper-link link-secondary" href="/assets/AAAI21 Oral PPT.pdf" target="_blank" rel="noopener noreferrer">Slides</a>
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||||||
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</div>
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||||||
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</div>
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||||||
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<h5 class="mb-1 paper-title">Pre-training Context and Time Aware Location Embeddings from Spatial-Temporal Trajectories for User Next Location Prediction</h5>
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</div>
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<footer>
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Designed and implemented by Yan Lin.
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<div class="page-header-logo h2 m-0" style="font-family: Impact, 'Arial Black', 'Franklin Gothic Bold', sans-serif;">Yan Lin's Projects</div>
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Fundamental Research Funds for the Central Universities of China
|
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</p>
|
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<div class="d-flex gap-2">
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||||||
|
<h5 class="mb-1 paper-title">Research on <i>Prediction of User Travel Destination and Travel Time Based on Trajectory Representation Learning</i></h5>
|
||||||
|
<p class="card-text mb-auto project-desc">Applies representation learning to trajectory data to transform original features into high-level information, improving the performance of downstream tasks such as travel time and destination prediction.</p>
|
||||||
|
</div>
|
||||||
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|
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|
||||||
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<p class="d-inline-block mb-0 venue-name primary-text">
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Personal Interest Project
|
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</p>
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<div class="d-flex gap-2">
|
||||||
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|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://www.overleafcopilot.com/" target="_blank" rel="noopener noreferrer">Home</a>
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://chromewebstore.google.com/detail/overleaf-copilot/eoadabdpninlhkkbhngoddfjianhlghb" target="_blank" rel="noopener noreferrer">Install</a>
|
||||||
|
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
|
<h5 class="mb-1 paper-title">Development of <i>OverleafCopilot - Empowering Academic Writing in Overleaf with Large Language Models</i></h5>
|
||||||
|
<p class="card-text mb-auto project-desc">This project aims to develop a Browser extension to seamlessly integrate Large Language Models (such as ChatGPT) into the popular online academic writing platform, Overleaf.</p>
|
||||||
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</div>
|
||||||
|
|
||||||
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|
||||||
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|
||||||
|
<div class="list-group-item px-0">
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||||||
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<div class="d-flex justify-content-between align-items-center mb-1">
|
||||||
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<p class="d-inline-block mb-0 venue-name primary-text">
|
||||||
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Personal Interest Project
|
||||||
|
</p>
|
||||||
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<div class="d-flex gap-2">
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://www.promptgenius.site/" target="_blank" rel="noopener noreferrer">Website</a>
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://github.com/wenhaomin/ChatGPT-PromptGenius" target="_blank" rel="noopener noreferrer">Code</a>
|
||||||
|
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
|
<h5 class="mb-1 paper-title">Development of <i>PromptGenius - All-purpose prompts for LLMs</i></h5>
|
||||||
|
<p class="card-text mb-auto project-desc">This project focuses on developing a website that offers a wide range of prompt categories, enhancing the versatility of LLMs for various tasks and improving their output quality.</p>
|
||||||
|
</div>
|
||||||
|
|
||||||
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<div class="list-group-item px-0">
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||||||
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<div class="d-flex justify-content-between align-items-center mb-1">
|
||||||
|
<p class="d-inline-block mb-0 venue-name secondary-text">
|
||||||
|
Villum Foundation
|
||||||
|
</p>
|
||||||
|
<div class="d-flex gap-2">
|
||||||
|
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
|
<h5 class="mb-1 paper-title">Research on <i>Inverse Design of Materials Using Diffusion Probabilistic Models</i></h5>
|
||||||
|
<p class="card-text mb-auto project-desc">This project focuses on developing diffusion probabilistic models to first understand the relationship between chemistry/structure and material properties, then enable the inverse design of new materials with specific properties. This project currently supports my postdoctoral research position.</p>
|
||||||
|
</div>
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
<div class="list-group-item px-0">
|
||||||
|
<div class="d-flex justify-content-between align-items-center mb-1">
|
||||||
|
<p class="d-inline-block mb-0 venue-name secondary-text">
|
||||||
|
National Natural Science Foundation of China
|
||||||
|
</p>
|
||||||
|
<div class="d-flex gap-2">
|
||||||
|
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
|
<h5 class="mb-1 paper-title">Research on <i>Pre-training Representation Learning Methods of Spatial-temporal Trajectory Data for Traffic Prediction</i></h5>
|
||||||
|
<p class="card-text mb-auto project-desc">This project aims to propose pre-training representation learning methods for spatial-temporal trajectory data, modeling multiple features to improve traffic prediction tasks. It demonstrates how trajectory representation learning can enhance traffic data mining.</p>
|
||||||
|
</div>
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
<div class="list-group-item px-0">
|
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<div class="d-flex justify-content-between align-items-center mb-1">
|
||||||
|
<p class="d-inline-block mb-0 venue-name secondary-text">
|
||||||
|
National Natural Science Foundation of China
|
||||||
|
</p>
|
||||||
|
<div class="d-flex gap-2">
|
||||||
|
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
|
<h5 class="mb-1 paper-title">Research on <i>Spatial-temporal Trajectory Generation and Representation Learning Methods for Sparsity Problems</i></h5>
|
||||||
|
<p class="card-text mb-auto project-desc">This project explores how to generate high-quality spatial-temporal trajectory data and corresponding representations to address sparsity-related issues, thereby supporting a variety of downstream tasks.</p>
|
||||||
|
</div>
|
||||||
|
|
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|
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<div class="page-header-logo h2 m-0" style="font-family: Impact, 'Arial Black', 'Franklin Gothic Bold', sans-serif;">Yan Lin's Publications</div>
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||||||
|
<span class="d-none d-md-inline">Presentations</span>
|
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|
</a>
|
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|
</li>
|
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|
<li class="nav-item">
|
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|
<a class="link nav-link px-0" href="/#services">
|
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|
<span class="d-inline d-md-none">Serve</span>
|
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|
<span class="d-none d-md-inline">Services</span>
|
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|
</a>
|
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|
</li>
|
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|
<li class="nav-item">
|
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|
<a class="link nav-link px-0" href="https://blog.yanlincs.com">
|
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|
<span class="d-inline d-md-none">Blog</span>
|
||||||
|
<span class="d-none d-md-inline">Blog</span>
|
||||||
|
</a>
|
||||||
|
</li>
|
||||||
|
</ul>
|
||||||
|
</nav> -->
|
||||||
|
|
||||||
|
</header>
|
||||||
|
|
||||||
|
|
||||||
|
<article class="section mt-4">
|
||||||
|
<div class="list-group list-group-flush">
|
||||||
|
|
||||||
|
|
||||||
|
<div class="list-group-item px-0">
|
||||||
|
<div class="d-flex justify-content-between align-items-center mb-1">
|
||||||
|
<p class="d-inline-block mb-0 venue-name primary-text">
|
||||||
|
IEEE TKDE<span class='text-muted'> | </span>2025
|
||||||
|
</p>
|
||||||
|
<div class="d-flex gap-2">
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://ieeexplore.ieee.org/document/11004614" target="_blank" rel="noopener noreferrer">Paper</a>
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://arxiv.org/abs/2402.07232" target="_blank" rel="noopener noreferrer">Preprint</a>
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://github.com/Logan-Lin/UVTM" target="_blank" rel="noopener noreferrer">Code</a>
|
||||||
|
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
|
<h5 class="mb-1 paper-title">UVTM: Universal Vehicle Trajectory Modeling with ST Feature Domain Generation</h5>
|
||||||
|
<p class="card-text mb-auto author-name"><strong>Yan Lin</strong>, Jilin Hu, Shengnan Guo, Bin Yang, Christian S. Jensen, Youfang Lin, Huaiyu Wan</p>
|
||||||
|
</div>
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
<div class="list-group-item px-0">
|
||||||
|
<div class="d-flex justify-content-between align-items-center mb-1">
|
||||||
|
<p class="d-inline-block mb-0 venue-name primary-text">
|
||||||
|
IJCAI<span class='text-muted'> | </span>2025
|
||||||
|
</p>
|
||||||
|
<div class="d-flex gap-2">
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://arxiv.org/abs/2405.12459" target="_blank" rel="noopener noreferrer">Preprint</a>
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://github.com/Zeru19/PLM4Traj" target="_blank" rel="noopener noreferrer">Code</a>
|
||||||
|
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
|
<h5 class="mb-1 paper-title">TrajCogn: Leveraging LLMs for Cognizing Movement Patterns and Travel Purposes from Trajectories</h5>
|
||||||
|
<p class="card-text mb-auto author-name">Zeyu Zhou*, <strong>Yan Lin*</strong>, Haomin Wen, Shengnan Guo, Jilin Hu, Youfang Lin, Huaiyu Wan</p>
|
||||||
|
</div>
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
<div class="list-group-item px-0">
|
||||||
|
<div class="d-flex justify-content-between align-items-center mb-1">
|
||||||
|
<p class="d-inline-block mb-0 venue-name primary-text">
|
||||||
|
IEEE TKDE<span class='text-muted'> | </span>2025
|
||||||
|
</p>
|
||||||
|
<div class="d-flex gap-2">
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://ieeexplore.ieee.org/document/10818577" target="_blank" rel="noopener noreferrer">Paper</a>
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://arxiv.org/abs/2407.12550" target="_blank" rel="noopener noreferrer">Preprint</a>
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://github.com/Logan-Lin/UniTE" target="_blank" rel="noopener noreferrer">Code</a>
|
||||||
|
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
|
<h5 class="mb-1 paper-title">UniTE: A Survey and Unified Pipeline for Pre-training Spatiotemporal Trajectory Embeddings</h5>
|
||||||
|
<p class="card-text mb-auto author-name"><strong>Yan Lin</strong>, Zeyu Zhou, Yicheng Liu, Haochen Lv, Haomin Wen, Tianyi Li, Yushuai Li, Christian S. Jensen, Shengnan Guo, Youfang Lin, Huaiyu Wan</p>
|
||||||
|
</div>
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
<div class="list-group-item px-0">
|
||||||
|
<div class="d-flex justify-content-between align-items-center mb-1">
|
||||||
|
<p class="d-inline-block mb-0 venue-name primary-text">
|
||||||
|
WWW<span class='text-muted'> | </span>2025
|
||||||
|
</p>
|
||||||
|
<div class="d-flex gap-2">
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://openreview.net/forum?id=KmMSQS6tFn" target="_blank" rel="noopener noreferrer">Paper</a>
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://github.com/decisionintelligence/Path-LLM" target="_blank" rel="noopener noreferrer">Code</a>
|
||||||
|
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
|
<h5 class="mb-1 paper-title">Path-LLM: A Multi-Modal Path Representation Learning by Aligning and Fusing with Large Language Models</h5>
|
||||||
|
<p class="card-text mb-auto author-name">Yongfu Wei*, <strong>Yan Lin*</strong>, Hongfan Gao, Ronghui Xu, Sean Bin Yang, Jilin Hu</p>
|
||||||
|
</div>
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
<div class="list-group-item px-0">
|
||||||
|
<div class="d-flex justify-content-between align-items-center mb-1">
|
||||||
|
<p class="d-inline-block mb-0 venue-name primary-text">
|
||||||
|
AAAI<span class='text-muted'> | </span>2025
|
||||||
|
</p>
|
||||||
|
<div class="d-flex gap-2">
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://arxiv.org/abs/2408.12809" target="_blank" rel="noopener noreferrer">Preprint</a>
|
||||||
|
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
|
<h5 class="mb-1 paper-title">DutyTTE: Deciphering Uncertainty in Origin-Destination Travel Time Estimation</h5>
|
||||||
|
<p class="card-text mb-auto author-name">Xiaowei Mao*, <strong>Yan Lin*</strong>, Shengnan Guo, Yubin Chen, Xingyu Xian, Haomin Wen, Qisen Xu, Youfang Lin, Huaiyu Wan</p>
|
||||||
|
</div>
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
<div class="list-group-item px-0">
|
||||||
|
<div class="d-flex justify-content-between align-items-center mb-1">
|
||||||
|
<p class="d-inline-block mb-0 venue-name primary-text">
|
||||||
|
NeurIPS<span class='text-muted'> | </span>2024
|
||||||
|
</p>
|
||||||
|
<div class="d-flex gap-2">
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://openreview.net/forum?id=0feJEykDRx" target="_blank" rel="noopener noreferrer">Paper</a>
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://neurips.cc/virtual/2024/poster/96914" target="_blank" rel="noopener noreferrer">Poster</a>
|
||||||
|
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
|
<h5 class="mb-1 paper-title">Mobility-LLM: Learning Visiting Intentions and Travel Preference from Human Mobility Data with Large Language Models</h5>
|
||||||
|
<p class="card-text mb-auto author-name">Letian Gong*, <strong>Yan Lin*</strong>, Xinyue Zhang, Yiwen Lu, Xuedi Han, Yichen Liu, Shengnan Guo, Youfang Lin, Huaiyu Wan</p>
|
||||||
|
</div>
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
<div class="list-group-item px-0">
|
||||||
|
<div class="d-flex justify-content-between align-items-center mb-1">
|
||||||
|
<p class="d-inline-block mb-0 venue-name primary-text">
|
||||||
|
SIGMOD<span class='text-muted'> | </span>2024
|
||||||
|
</p>
|
||||||
|
<div class="d-flex gap-2">
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://dl.acm.org/doi/10.1145/3617337" target="_blank" rel="noopener noreferrer">Paper</a>
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://arxiv.org/abs/2307.03048" target="_blank" rel="noopener noreferrer">Preprint</a>
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://github.com/Logan-Lin/DOT" target="_blank" rel="noopener noreferrer">Code</a>
|
||||||
|
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
|
<h5 class="mb-1 paper-title">Origin-Destination Travel Time Oracle for Map-based Services</h5>
|
||||||
|
<p class="card-text mb-auto author-name"><strong>Yan Lin</strong>, Huaiyu Wan, Jilin Hu, Shengnan Guo, Bin Yang, Christian S. Jensen, Youfang Lin</p>
|
||||||
|
</div>
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
<div class="list-group-item px-0">
|
||||||
|
<div class="d-flex justify-content-between align-items-center mb-1">
|
||||||
|
<p class="d-inline-block mb-0 venue-name primary-text">
|
||||||
|
IEEE TKDE<span class='text-muted'> | </span>2023
|
||||||
|
</p>
|
||||||
|
<div class="d-flex gap-2">
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://ieeexplore.ieee.org/abstract/document/10375102" target="_blank" rel="noopener noreferrer">Paper</a>
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://arxiv.org/abs/2207.14539" target="_blank" rel="noopener noreferrer">Preprint</a>
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://github.com/Logan-Lin/MMTEC" target="_blank" rel="noopener noreferrer">Code</a>
|
||||||
|
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
|
<h5 class="mb-1 paper-title">Pre-training General Trajectory Embeddings with Maximum Multi-view Entropy Coding</h5>
|
||||||
|
<p class="card-text mb-auto author-name"><strong>Yan Lin</strong>, Huaiyu Wan, Shengnan Guo, Jilin Hu, Christian S. Jensen, Youfang Lin</p>
|
||||||
|
</div>
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
<div class="list-group-item px-0">
|
||||||
|
<div class="d-flex justify-content-between align-items-center mb-1">
|
||||||
|
<p class="d-inline-block mb-0 venue-name primary-text">
|
||||||
|
IEEE TKDE<span class='text-muted'> | </span>2022
|
||||||
|
</p>
|
||||||
|
<div class="d-flex gap-2">
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://ieeexplore.ieee.org/abstract/document/9351627" target="_blank" rel="noopener noreferrer">Paper</a>
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://github.com/Logan-Lin/TALE" target="_blank" rel="noopener noreferrer">Code</a>
|
||||||
|
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
|
<h5 class="mb-1 paper-title">Pre-training Time-aware location embeddings from spatial-temporal trajectories</h5>
|
||||||
|
<p class="card-text mb-auto author-name">Huaiyu Wan, <strong>Yan Lin</strong>, Shengnan Guo, Youfang Lin</p>
|
||||||
|
</div>
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
<div class="list-group-item px-0">
|
||||||
|
<div class="d-flex justify-content-between align-items-center mb-1">
|
||||||
|
<p class="d-inline-block mb-0 venue-name primary-text">
|
||||||
|
AAAI<span class='text-muted'> | </span>2021
|
||||||
|
</p>
|
||||||
|
<div class="d-flex gap-2">
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://ojs.aaai.org/index.php/AAAI/article/view/16548" target="_blank" rel="noopener noreferrer">Paper</a>
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://github.com/Logan-Lin/CTLE" target="_blank" rel="noopener noreferrer">Code</a>
|
||||||
|
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
|
<h5 class="mb-1 paper-title">Pre-training Context and Time Aware Location Embeddings from Spatial-Temporal Trajectories for User Next Location Prediction</h5>
|
||||||
|
<p class="card-text mb-auto author-name"><strong>Yan Lin</strong>, Huaiyu Wan, Shengnan Guo, Youfang Lin</p>
|
||||||
|
</div>
|
||||||
|
|
||||||
|
|
||||||
|
</div>
|
||||||
|
<hr class="my-2" />
|
||||||
|
<div class="list-group list-group-flush">
|
||||||
|
|
||||||
|
|
||||||
|
<div class="list-group-item px-0">
|
||||||
|
<div class="d-flex justify-content-between align-items-center mb-1">
|
||||||
|
<p class="d-inline-block mb-0 venue-name secondary-text">
|
||||||
|
KDD<span class='text-muted'> | </span>2025
|
||||||
|
</p>
|
||||||
|
<div class="d-flex gap-2">
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://arxiv.org/abs/2412.10859" target="_blank" rel="noopener noreferrer">Preprint</a>
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://github.com/decisionintelligence/DUET" target="_blank" rel="noopener noreferrer">Code</a>
|
||||||
|
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
|
<h5 class="mb-1 paper-title">DUET: Dual Clustering Enhanced Multivariate Time Series Forecasting</h5>
|
||||||
|
<p class="card-text mb-auto author-name">Xiangfei Qiu, Xingjian Wu, <strong>Yan Lin</strong>, Chenjuan Guo, Jilin Hu, Bin Yang</p>
|
||||||
|
</div>
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
<div class="list-group-item px-0">
|
||||||
|
<div class="d-flex justify-content-between align-items-center mb-1">
|
||||||
|
<p class="d-inline-block mb-0 venue-name secondary-text">
|
||||||
|
IEEE TKDE<span class='text-muted'> | </span>2024
|
||||||
|
</p>
|
||||||
|
<div class="d-flex gap-2">
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://www.computer.org/csdl/journal/tk/5555/01/10679607/20b3hlbjBOo" target="_blank" rel="noopener noreferrer">Paper</a>
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://arxiv.org/abs/2402.07369" target="_blank" rel="noopener noreferrer">Preprint</a>
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://github.com/wtl52656/Diff-RNTraj" target="_blank" rel="noopener noreferrer">Code</a>
|
||||||
|
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
|
<h5 class="mb-1 paper-title">Diff-RNTraj: A Structure-aware Diffusion Model for Road Network-constrained Trajectory Generation</h5>
|
||||||
|
<p class="card-text mb-auto author-name">Tonglong Wei, Youfang Lin, Shengnan Guo, <strong>Yan Lin</strong>, Yiheng Huang, Chenyang Xiang, Yuqing Bai, Menglu Ya, Huaiyu Wan</p>
|
||||||
|
</div>
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
<div class="list-group-item px-0">
|
||||||
|
<div class="d-flex justify-content-between align-items-center mb-1">
|
||||||
|
<p class="d-inline-block mb-0 venue-name secondary-text">
|
||||||
|
IEEE TKDE<span class='text-muted'> | </span>2024
|
||||||
|
</p>
|
||||||
|
<div class="d-flex gap-2">
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://ieeexplore.ieee.org/document/10836764" target="_blank" rel="noopener noreferrer">Paper</a>
|
||||||
|
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
|
<h5 class="mb-1 paper-title">STCDM: Spatio-Temporal Contrastive Diffusion Model for Check-In Sequence Generation</h5>
|
||||||
|
<p class="card-text mb-auto author-name">Letian Gong, Shengnan Guo, <strong>Yan Lin</strong>, Yichen Liu, Erwen Zheng, Yiwei Shuang, Youfang Lin, Jilin Hu, Huaiyu Wan</p>
|
||||||
|
</div>
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
<div class="list-group-item px-0">
|
||||||
|
<div class="d-flex justify-content-between align-items-center mb-1">
|
||||||
|
<p class="d-inline-block mb-0 venue-name secondary-text">
|
||||||
|
IEEE TKDE<span class='text-muted'> | </span>2024
|
||||||
|
</p>
|
||||||
|
<div class="d-flex gap-2">
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://www.computer.org/csdl/journal/tk/5555/01/10517676/1WCj0j0FljW" target="_blank" rel="noopener noreferrer">Paper</a>
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://arxiv.org/abs/2404.19141" target="_blank" rel="noopener noreferrer">Preprint</a>
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://github.com/wtl52656/MM-STGED" target="_blank" rel="noopener noreferrer">Code</a>
|
||||||
|
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
|
<h5 class="mb-1 paper-title">Micro-Macro Spatial-Temporal Graph-based Encoder-Decoder for Map-Constrained Trajectory Recovery</h5>
|
||||||
|
<p class="card-text mb-auto author-name">Tonglong Wei, Youfang Lin, <strong>Yan Lin</strong>, Shengnan Guo, Lan Zhang, Huaiyu Wan</p>
|
||||||
|
</div>
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
<div class="list-group-item px-0">
|
||||||
|
<div class="d-flex justify-content-between align-items-center mb-1">
|
||||||
|
<p class="d-inline-block mb-0 venue-name secondary-text">
|
||||||
|
KBS<span class='text-muted'> | </span>2024
|
||||||
|
</p>
|
||||||
|
<div class="d-flex gap-2">
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://www.sciencedirect.com/science/article/pii/S0950705123010730" target="_blank" rel="noopener noreferrer">Paper</a>
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://github.com/wtl52656/IAGCN" target="_blank" rel="noopener noreferrer">Code</a>
|
||||||
|
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
|
<h5 class="mb-1 paper-title">Inductive and Adaptive Graph Convolution Networks Equipped with Constraint Task for Spatial-Temporal Traffic Data Kriging</h5>
|
||||||
|
<p class="card-text mb-auto author-name">Tonglong Wei, Youfang Lin, Shengnan Guo, <strong>Yan Lin</strong>, Yiji Zhao, Xiyuan Jin, Zhihao Wu, Huaiyu Wan</p>
|
||||||
|
</div>
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
<div class="list-group-item px-0">
|
||||||
|
<div class="d-flex justify-content-between align-items-center mb-1">
|
||||||
|
<p class="d-inline-block mb-0 venue-name secondary-text">
|
||||||
|
IEEE TKDE<span class='text-muted'> | </span>2024
|
||||||
|
</p>
|
||||||
|
<div class="d-flex gap-2">
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://arxiv.org/abs/2407.15899" target="_blank" rel="noopener noreferrer">Preprint</a>
|
||||||
|
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
|
<h5 class="mb-1 paper-title">Spatial-Temporal Cross-View Contrastive Pre-Training for Check-in Sequence Representation Learning</h5>
|
||||||
|
<p class="card-text mb-auto author-name">Letian Gong, Huaiyu Wan, Shengnan Guo, Li Xiucheng, <strong>Yan Lin</strong>, Erwen Zheng, Tianyi Wang, Zeyu Zhou, Youfang Lin</p>
|
||||||
|
</div>
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
<div class="list-group-item px-0">
|
||||||
|
<div class="d-flex justify-content-between align-items-center mb-1">
|
||||||
|
<p class="d-inline-block mb-0 venue-name secondary-text">
|
||||||
|
AAAI<span class='text-muted'> | </span>2023
|
||||||
|
</p>
|
||||||
|
<div class="d-flex gap-2">
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://ojs.aaai.org/index.php/AAAI/article/view/25546" target="_blank" rel="noopener noreferrer">Paper</a>
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://github.com/LetianGong/CACSR" target="_blank" rel="noopener noreferrer">Code</a>
|
||||||
|
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
|
<h5 class="mb-1 paper-title">Contrastive Pre-training with Adversarial Perturbations for Check-In Sequence Representation Learning</h5>
|
||||||
|
<p class="card-text mb-auto author-name">Letian Gong, Youfang Lin, Shengnan Guo, <strong>Yan Lin</strong>, Tianyi Wang, Erwen Zheng, Zeyu Zhou, Huaiyu Wan</p>
|
||||||
|
</div>
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
<div class="list-group-item px-0">
|
||||||
|
<div class="d-flex justify-content-between align-items-center mb-1">
|
||||||
|
<p class="d-inline-block mb-0 venue-name secondary-text">
|
||||||
|
ESWA<span class='text-muted'> | </span>2023
|
||||||
|
</p>
|
||||||
|
<div class="d-flex gap-2">
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://www.sciencedirect.com/science/article/pii/S0957417423012241" target="_blank" rel="noopener noreferrer">Paper</a>
|
||||||
|
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
|
<h5 class="mb-1 paper-title">Adversarial Self-Attentive Time-Variant Neural Networks for Multi-Step Time Series Forecasting</h5>
|
||||||
|
<p class="card-text mb-auto author-name">Changxia Gao, Ning Zhang, Youru Li, <strong>Yan Lin</strong>, Huaiyu Wan</p>
|
||||||
|
</div>
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
<div class="list-group-item px-0">
|
||||||
|
<div class="d-flex justify-content-between align-items-center mb-1">
|
||||||
|
<p class="d-inline-block mb-0 venue-name secondary-text">
|
||||||
|
APIN<span class='text-muted'> | </span>2023
|
||||||
|
</p>
|
||||||
|
<div class="d-flex gap-2">
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://link.springer.com/article/10.1007/s10489-023-05057-7" target="_blank" rel="noopener noreferrer">Paper</a>
|
||||||
|
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
|
<h5 class="mb-1 paper-title">Multi-scale Adaptive Attention-based Time-Variant Neural Networks for Multi-step Time Series Forecasting</h5>
|
||||||
|
<p class="card-text mb-auto author-name">Changxia Gao, Ning Zhang, Youru Li, <strong>Yan Lin</strong>, Huaiyu Wan</p>
|
||||||
|
</div>
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
<div class="list-group-item px-0">
|
||||||
|
<div class="d-flex justify-content-between align-items-center mb-1">
|
||||||
|
<p class="d-inline-block mb-0 venue-name secondary-text">
|
||||||
|
NeurIPS<span class='text-muted'> | </span>2023
|
||||||
|
</p>
|
||||||
|
<div class="d-flex gap-2">
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://openreview.net/forum?id=y08bkEtNBK" target="_blank" rel="noopener noreferrer">Paper</a>
|
||||||
|
|
||||||
|
<a class="link icon-link icon-link-hover paper-link link-secondary" href="https://github.com/Water2sea/WITRAN" target="_blank" rel="noopener noreferrer">Code</a>
|
||||||
|
|
||||||
|
</div>
|
||||||
|
</div>
|
||||||
|
<h5 class="mb-1 paper-title">WITRAN: Water-wave Information Transmission and Recurrent Acceleration Network for Long-range Time Series Forecasting</h5>
|
||||||
|
<p class="card-text mb-auto author-name">Yuxin Jia, Youfang Lin, Xinyan Hao, <strong>Yan Lin</strong>, Shengnan Guo, Huaiyu Wan</p>
|
||||||
|
</div>
|
||||||
|
|
||||||
|
|
||||||
|
</div>
|
||||||
|
|
||||||
|
<div class="text-start mt-3">
|
||||||
|
<small class="text-muted" style="font-size: 0.8rem;">* Equal Contribution</small>
|
||||||
|
</div>
|
||||||
|
</article>
|
||||||
|
|
||||||
|
</main>
|
||||||
|
|
||||||
|
<footer>
|
||||||
|
<div class="container">
|
||||||
|
<p class="text-center text-secondary footer-text">
|
||||||
|
Designed and implemented by Yan Lin.
|
||||||
|
</p>
|
||||||
|
</div>
|
||||||
|
</footer>
|
||||||
|
|
||||||
|
<button id="back-to-top" class="btn btn-light rounded-circle d-none align-items-center justify-content-center" style="position: fixed; bottom: 20px; right: 20px; display: none; z-index: 1000; width: 40px; height: 40px; padding: 0;">
|
||||||
|
<svg xmlns="http://www.w3.org/2000/svg" width="1em" height="1em" fill="currentColor" class="bi bi-chevron-up" viewBox="0 0 16 16">
|
||||||
|
<path fill-rule="evenodd" d="M7.646 4.646a.5.5 0 0 1 .708 0l6 6a.5.5 0 0 1-.708.708L8 5.707l-5.646 5.647a.5.5 0 0 1-.708-.708z"/>
|
||||||
|
</svg>
|
||||||
|
</button>
|
||||||
|
|
||||||
|
|
||||||
|
<script>
|
||||||
|
// Show or hide the back-to-top button
|
||||||
|
window.addEventListener('scroll', function() {
|
||||||
|
var backToTopButton = document.getElementById('back-to-top');
|
||||||
|
if (window.scrollY > 100) {
|
||||||
|
backToTopButton.classList.remove('d-none');
|
||||||
|
backToTopButton.classList.add('d-flex');
|
||||||
|
} else {
|
||||||
|
backToTopButton.classList.add('d-none');
|
||||||
|
backToTopButton.classList.remove('d-flex');
|
||||||
|
}
|
||||||
|
});
|
||||||
|
|
||||||
|
// Scroll to top when the button is clicked
|
||||||
|
document.getElementById('back-to-top').addEventListener('click', function(e) {
|
||||||
|
e.preventDefault();
|
||||||
|
window.scrollTo({
|
||||||
|
top: 0,
|
||||||
|
behavior: 'smooth'
|
||||||
|
});
|
||||||
|
window.location.href = '#';
|
||||||
|
return false;
|
||||||
|
});
|
||||||
|
</script>
|
||||||
|
|
||||||
|
</body>
|
||||||
|
|
||||||
|
</html>
|
||||||
|
|
@ -5,13 +5,17 @@
|
||||||
<meta charset="UTF-8">
|
<meta charset="UTF-8">
|
||||||
<meta name="viewport" content="width=device-width, initial-scale=1.0">
|
<meta name="viewport" content="width=device-width, initial-scale=1.0">
|
||||||
<title>{% block title %}Yan Lin{% endblock %}</title>
|
<title>{% block title %}Yan Lin{% endblock %}</title>
|
||||||
<link rel="icon" href="/favicon-dark.webp" type="image/webp">
|
|
||||||
<link rel="icon" href="/favicon-dark.webp" type="image/webp" media="(prefers-color-scheme: light)">
|
|
||||||
<link rel="icon" href="/favicon-light.webp" type="image/webp" media="(prefers-color-scheme: dark)">
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|
||||||
<link href="/css/bootstrap.min.css" rel="stylesheet">
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|
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<link rel="stylesheet" href="/css/index.css">
|
|
||||||
<script defer src="https://tracker.yanlincs.com/script.js" data-website-id="39b2ce27-b581-4c54-8f2d-ff7dbaeb70cc"></script>
|
<script defer src="https://tracker.yanlincs.com/script.js" data-website-id="39b2ce27-b581-4c54-8f2d-ff7dbaeb70cc"></script>
|
||||||
|
|
||||||
|
<link rel="icon" type="image/png" href="/favicon/favicon-96x96.png" sizes="96x96" />
|
||||||
|
<link rel="icon" type="image/svg+xml" href="/favicon/favicon.svg" />
|
||||||
|
<link rel="shortcut icon" href="/favicon/favicon.ico" />
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|
<link rel="apple-touch-icon" sizes="180x180" href="/favicon/apple-touch-icon.png" />
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|
<meta name="apple-mobile-web-app-title" content="YL Homepage" />
|
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|
<link rel="manifest" href="/favicon/site.webmanifest" />
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||||||
|
|
||||||
|
<link href="/css/bootstrap.min.css" rel="stylesheet">
|
||||||
|
<link rel="stylesheet" href="/css/index.css">
|
||||||
{% block extra_head %}{% endblock %}
|
{% block extra_head %}{% endblock %}
|
||||||
</head>
|
</head>
|
||||||
|
|
||||||
|
|
|
||||||
Loading…
Add table
Add a link
Reference in a new issue