Derek Lim

According to our database, Derek Lim authored at least 22 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Learning on LoRAs: GL-Equivariant Processing of Low-Rank Weight Spaces for Large Finetuned Models.

Moe Putterman, Derek Lim, Yoav Gelberg, Stefanie Jegelka, Haggai Maron

CoRR, 2024

The Empirical Impact of Neural Parameter Symmetries, or Lack Thereof.

Derek Lim, Moe Putterman, Robin Walters, Haggai Maron, Stefanie Jegelka

CoRR, 2024

A Canonization Perspective on Invariant and Equivariant Learning.

George Ma, Yifei Wang, Derek Lim, Stefanie Jegelka, Yisen Wang

CoRR, 2024

Future Directions in Foundations of Graph Machine Learning.

Christopher Morris, Nadav Dym, Haggai Maron, Ismail Ilkan Ceylan, Fabrizio Frasca, Ron Levie, Derek Lim, Michael M. Bronstein, Martin Grohe, Stefanie Jegelka

CoRR, 2024

Position: Future Directions in the Theory of Graph Machine Learning.

Christopher Morris, Fabrizio Frasca, Nadav Dym, Haggai Maron, Ismail Ilkan Ceylan, Ron Levie, Derek Lim, Michael M. Bronstein, Martin Grohe, Stefanie Jegelka

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Graph Metanetworks for Processing Diverse Neural Architectures.

Derek Lim, Haggai Maron, Marc T. Law, Jonathan Lorraine, James Lucas

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Structuring Representation Geometry with Rotationally Equivariant Contrastive Learning.

Sharut Gupta, Joshua Robinson, Derek Lim, Soledad Villar, Stefanie Jegelka

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Expressive Sign Equivariant Networks for Spectral Geometric Learning.

Derek Lim, Joshua Robinson, Stefanie Jegelka, Haggai Maron

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Equivariant Polynomials for Graph Neural Networks.

Omri Puny, Derek Lim, Bobak Toussi Kiani, Haggai Maron, Yaron Lipman

Proceedings of the International Conference on Machine Learning, 2023

Graph Inductive Biases in Transformers without Message Passing.

Liheng Ma, Chen Lin, Derek Lim, Adriana Romero-Soriano, Puneet K. Dokania, Mark Coates, Philip H. S. Torr, Ser-Nam Lim

Proceedings of the International Conference on Machine Learning, 2023

Sign and Basis Invariant Networks for Spectral Graph Representation Learning.

Derek Lim, Joshua David Robinson, Lingxiao Zhao, Tess E. Smidt, Suvrit Sra, Haggai Maron, Stefanie Jegelka

Proceedings of the Eleventh International Conference on Learning Representations, 2023

The Power of Recursion in Graph Neural Networks for Counting Substructures.

Behrooz Tahmasebi, Derek Lim, Stefanie Jegelka

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

The Doubly Stochastic Single Eigenvalue Problem: A Computational Approach.

Amit Harlev, Charles R. Johnson, Derek Lim

Exp. Math., 2022

The First Learning on Graphs Conference: Preface.

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

Proceedings of the Learning on Graphs Conference, 2022

Understanding Doubly Stochastic Clustering.

Tianjiao Ding, Derek Lim, René Vidal, Benjamin D. Haeffele

Proceedings of the International Conference on Machine Learning, 2022

Equivariant Subgraph Aggregation Networks.

Beatrice Bevilacqua, Fabrizio Frasca, Derek Lim, Balasubramaniam Srinivasan, Chen Cai, Gopinath Balamurugan, Michael M. Bronstein, Haggai Maron

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

New Benchmarks for Learning on Non-Homophilous Graphs.

Derek Lim, Xiuyu Li, Felix Hohne, Ser-Nam Lim

CoRR, 2021

Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods.

Derek Lim, Felix Hohne, Xiuyu Li, Sijia Linda Huang, Vaishnavi Gupta, Omkar Bhalerao, Ser-Nam Lim

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Equivariant Manifold Flows.

Isay Katsman, Aaron Lou, Derek Lim, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Expertise and Dynamics within Crowdsourced Musical Knowledge Curation: A Case Study of the Genius Platform.

Derek Lim, Austin R. Benson

Proceedings of the Fifteenth International AAAI Conference on Web and Social Media, 2021

2020

Doubly Stochastic Subspace Clustering.

Derek Lim, René Vidal, Benjamin D. Haeffele

CoRR, 2020

Neural Manifold Ordinary Differential Equations.

Aaron Lou, Derek Lim, Isay Katsman, Leo Huang, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020