Derek Lim

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 31

Top Topics

Subspace Clustering

Message Passing

Tree Reweighted

Neural Architectures

Top Venues

Publications

Derek Lim, Moe Putterman, Robin Walters, Haggai Maron, Stefanie Jegelka
The Empirical Impact of Neural Parameter Symmetries, or Lack Thereof. CoRR (2024)
Sharut Gupta, Joshua Robinson, Derek Lim, Soledad Villar, Stefanie Jegelka
Structuring Representation Geometry with Rotationally Equivariant Contrastive Learning. ICLR (2024)
Derek Lim, Haggai Maron, Marc T. Law, Jonathan Lorraine, James Lucas
Graph Metanetworks for Processing Diverse Neural Architectures. ICLR (2024)
George Ma, Yifei Wang, Derek Lim, Stefanie Jegelka, Yisen Wang
A Canonization Perspective on Invariant and Equivariant Learning. CoRR (2024)
Christopher Morris, Nadav Dym, Haggai Maron, Ismail Ilkan Ceylan, Fabrizio Frasca, Ron Levie, Derek Lim, Michael Bronstein, Martin Grohe, Stefanie Jegelka
Future Directions in Foundations of Graph Machine Learning. CoRR (2024)
Sharut Gupta, Joshua Robinson, Derek Lim, Soledad Villar, Stefanie Jegelka
Structuring Representation Geometry with Rotationally Equivariant Contrastive Learning. CoRR (2023)
Derek Lim, Joshua David Robinson, Lingxiao Zhao, Tess E. Smidt, Suvrit Sra, Haggai Maron, Stefanie Jegelka
Sign and Basis Invariant Networks for Spectral Graph Representation Learning. ICLR (2023)
Liheng Ma, Chen Lin, Derek Lim, Adriana Romero-Soriano, Puneet K. Dokania, Mark Coates, Philip H. S. Torr, Ser-Nam Lim
Graph Inductive Biases in Transformers without Message Passing. CoRR (2023)
Derek Lim, Joshua Robinson, Stefanie Jegelka, Haggai Maron
Expressive Sign Equivariant Networks for Spectral Geometric Learning. NeurIPS (2023)
Liheng Ma, Chen Lin, Derek Lim, Adriana Romero-Soriano, Puneet K. Dokania, Mark Coates, Philip H. S. Torr, Ser-Nam Lim
Graph Inductive Biases in Transformers without Message Passing. ICML (2023)
Derek Lim, Joshua Robinson, Stefanie Jegelka, Haggai Maron
Expressive Sign Equivariant Networks for Spectral Geometric Learning. CoRR (2023)
Omri Puny, Derek Lim, Bobak Toussi Kiani, Haggai Maron, Yaron Lipman
Equivariant Polynomials for Graph Neural Networks. CoRR (2023)
Behrooz Tahmasebi, Derek Lim, Stefanie Jegelka
The Power of Recursion in Graph Neural Networks for Counting Substructures. AISTATS (2023)
Omri Puny, Derek Lim, Bobak Toussi Kiani, Haggai Maron, Yaron Lipman
Equivariant Polynomials for Graph Neural Networks. ICML (2023)
Derek Lim, Haggai Maron, Marc T. Law, Jonathan Lorraine, James Lucas
Graph Metanetworks for Processing Diverse Neural Architectures. CoRR (2023)
Beatrice Bevilacqua, Fabrizio Frasca, Derek Lim, Balasubramaniam Srinivasan, Chen Cai, Gopinath Balamurugan, Michael M. Bronstein, Haggai Maron
Equivariant Subgraph Aggregation Networks. ICLR (2022)
Amit Harlev, Charles R. Johnson, Derek Lim
The Doubly Stochastic Single Eigenvalue Problem: A Computational Approach. Exp. Math. 31 (3) (2022)
Bastian Rieck, Razvan Pascanu, Yuanqi Du, Hannes Stärk, Derek Lim, Chaitanya K. Joshi, Andreea Deac, Iulia Duta, Joshua Robinson, Gabriele Corso, Leonardo Cotta, Yanqiao Zhu, Kexin Huang, Michelle M. Li, Sofia Bourhim, Ilia Igashov
The First Learning on Graphs Conference: Preface. LoG (2022)
Derek Lim, Joshua Robinson, Lingxiao Zhao, Tess Smidt, Suvrit Sra, Haggai Maron, Stefanie Jegelka
Sign and Basis Invariant Networks for Spectral Graph Representation Learning. CoRR (2022)
Tianjiao Ding, Derek Lim, René Vidal, Benjamin D. Haeffele
Understanding Doubly Stochastic Clustering. ICML (2022)
Derek Lim, Xiuyu Li, Felix Hohne, Ser-Nam Lim
New Benchmarks for Learning on Non-Homophilous Graphs. CoRR (2021)
Isay Katsman, Aaron Lou, Derek Lim, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa
Equivariant Manifold Flows. CoRR (2021)
Derek Lim, Austin R. Benson
Expertise and Dynamics within Crowdsourced Musical Knowledge Curation: A Case Study of the Genius Platform. ICWSM (2021)
Beatrice Bevilacqua, Fabrizio Frasca, Derek Lim, Balasubramaniam Srinivasan, Chen Cai, Gopinath Balamurugan, Michael M. Bronstein, Haggai Maron
Equivariant Subgraph Aggregation Networks. CoRR (2021)
Derek Lim, Felix Hohne, Xiuyu Li, Sijia Linda Huang, Vaishnavi Gupta, Omkar Bhalerao, Ser-Nam Lim
Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods. NeurIPS (2021)
Isay Katsman, Aaron Lou, Derek Lim, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa
Equivariant Manifold Flows. NeurIPS (2021)
Derek Lim, Felix Hohne, Xiuyu Li, Sijia Linda Huang, Vaishnavi Gupta, Omkar Bhalerao, Ser-Nam Lim
Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods. CoRR (2021)
Aaron Lou, Derek Lim, Isay Katsman, Leo Huang, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa
Neural Manifold Ordinary Differential Equations. CoRR (2020)
Aaron Lou, Derek Lim, Isay Katsman, Leo Huang, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa
Neural Manifold Ordinary Differential Equations. NeurIPS (2020)
Derek Lim, René Vidal, Benjamin D. Haeffele
Doubly Stochastic Subspace Clustering. CoRR (2020)
Derek Lim, Austin R. Benson
Expertise and Dynamics within Crowdsourced Musical Knowledge Curation: A Case Study of the Genius Platform. CoRR (2020)