Conference Poster
The Learning on Graphs conference (LoG) is an annual research conference that covers areas broadly related to machine learning on graphs and geometry, with a special focus on review quality. In its inaugural edition, LoG 2022 received 250+ paper submissions, 2,800+ total registrations, and distributed $30,000+ in reviewer awards.
The Log 2024 meeting up will take place at Duke Kunshan University:
Time Table |
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|---|---|---|---|
| Time | Session | Speaker | Talk Title |
| Day 1: 29 November 2024, Friday | |||
| 9:00-9:15 | Opening Remarks | LoG Organizer | |
| 9:15-10:00 | Keynote Talk | Zhewei Wei | Graph Machine Learning: Foundations and Perspectives |
| 10:30-11:00 | Invited Talk | Xian Wei | Geometric Transformer Learning for Point Clouds |
| 11:00-11:30 | Invited Talk | Eric Qu | The Importance of Being Scalable: Improving the Speed and Accuracy of Neural Network Interatomic Potentials |
| 11:30-12:00 | Invited Talk | Kun Zhan | Bias Mitigation in Graph Generative Models |
| 14:00-14:45 | Keynote Talk | Angelica Aviles-Rivero | Hypergraphs Networks: Hybrid Models with Minimal Supervision for Multi-Modal Classification |
| 14:45-15:15 | Invited Talk | Chieh-Hsin Lai | Evolution of Diffusion Models: From Birth to Enhanced Efficiency and Controllability |
| 15:45-16:30 | Invited Talk | Cheng Cheng | Random Sampling and Distributed Reconstruction of Bandlimited Graph Signals from Local Measurements |
| 16:30-17:30 | Invited Talk | Zhixun Li | Graph Intelligence with Large Language Models and Prompt Learning |
| Day 2: 30 November 2024, Saturday | |||
| 9:00-9:45 | Keynote Talk | Shi Jin | Allen-Cahn Message Passing in Graph Neural Networks and Fast Sinkhorn for Wasserstein-1 Metric |
| 9:45-10:15 | Invited Talk | Ming Li | Heterophilous Hypergraph Learning |
| 10:45-11:30 | Keynote Talk | Chuan Shi | Graph Machine Learning: From Graph Neural Network to Graph Foundation Model |
| 11:30-12:00 | Invited Talk | Weiran Cai | Contrastive Learning for Homophilic and Heterophilic Graphs |
| 14:00-14:45 | Keynote Talk | Xiaosheng Zhuang | Permutation Equivariant Graph Framelets for Heterophilous Graph Learning |
| 14:45-15:15 | Invited Talk | Xiao He | ChemGPT: An AI-Driven Molecular Synthesis Platform |
| 15:45-16:15 | Invited Talk | Qingyun Sun | Towards Low-Distortion Graph Representation Learning |
| 16:15-16:45 | Invited Talk | Jian Jiang | Virtual Screening in Drug Design based on Topology and AI |
| 16:45-17:15 | Invited Talk | Teng Zhao | TBD |
| Day 3: 1 December 2024, Sunday | |||
| 9:00-9:45 | Keynote Talk | Guowei Wei | Topological Deep Learning on Graphs, Manifolds, and Curves |
| 9:45-10:15 | Invited Talk | Jiawei Jiang | 自监督图数据集压缩 |
| 10:45-11:15 | Invited Talk | Yuanhong Jiang | 图网络在推荐系统中的应用 |
| 11:15-11:45 | Invited Talk | Guibin Zhang | Graph4LLM: Reimagining Graph Machine Learning within LLM-based Agentic Systems |
| 11:45-12:15 | Invited Talk | Bohang Zhang | 图同态：研究图神经网络表达能力的定量框架 |
