Research Papers

* Denotes equal contribution or alphabetical authorship.

Graph Metanetworks for Processing Diverse Neural Architectures
Derek Lim, Haggai Maron, Marc T. Law, Jonathan Lorraine, James Lucas
ICLR, Spotlight (2024)
Structuring Representation Geometry with Rotationally Equivariant Contrastive Learning
Sharut Gupta*, Joshua Robinson*, Derek Lim, Soledad Villar, Stefanie Jegelka
ICLR (2024)
[arXiv] [code]
Expressive Sign Equivariant Networks for Spectral Geometric Learning
Derek Lim, Joshua Robinson, Stefanie Jegelka, Haggai Maron
NeurIPS, Spotlight (2023)
[arXiv] [code]
Equivariant Polynomials for Graph Neural Networks
Omri Puny*, Derek Lim*, Bobak Kiani*, Haggai Maron, Yaron Lipman
ICML, Oral (2023)
[arXiv] [code]
Graph Inductive Biases in Transformers without Message Passing
Liheng Ma*, Chen Lin*, Derek Lim, Adriana Romero-Soriano, Puneet K. Dokania, Mark Coates, Philip Torr, Ser-Nam Lim
ICML (2023)
[arXiv] [code]
Sign and Basis Invariant Networks for Spectral Graph Representation Learning
Derek Lim*, Joshua Robinson*, Lingxiao Zhao, Tess Smidt, Suvrit Sra, Haggai Maron, Stefanie Jegelka
ICLR, Spotlight (2023)
[arXiv] [code] [workshop pdf] [LoGaG Reading Group Talk]
Understanding Doubly Stochastic Clustering
Tianjiao Ding, Derek Lim, René Vidal, Benjamin Haeffele
ICML (2022)
Equivariant Subgraph Aggregation Networks
Beatrice Bevilacqua*, Fabrizio Frasca*, Derek Lim*, Balasubramaniam Srinivasan, Chen Cai, Gopinath Balamurugan, Michael Bronstein, Haggai Maron
ICLR (2022), Spotlight (176 / 3391 submissions)
[pdf] [arXiv] [code]
[ML Street Talk Podcast] [WelcomeAIOverlords Interview] [LoGaG Reading Group Talk] [WeChat post (图与推荐)]
Counting Substructures with Higher-Order Graph Neural Networks: Possibility and Impossibility Results
Behrooz Tahmasebi, Derek Lim, Stefanie Jegelka
AISTATS, Oral (32 / 1689 submissions) (2023)
Equivariant Manifold Flows
Isay Katsman*, Aaron Lou*, Derek Lim*, Qingxuan Jiang*, Ser-Nam Lim, Christopher De Sa
NeurIPS (2021)
Also in ICML INNF Workshop (2021)
[workshop pdf]

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
NeurIPS (2021)
Previous version: New Benchmarks for Learning on Non-Homophilous Graphs
Workshop on Graph Learning Benchmarks (GLB 2021) at WWW (2021)
[workshop arXiv] [workshop pdf] [workshop data/code]

[arXiv] [data/code]
Doubly Stochastic Subspace Clustering
Derek Lim, René Vidal, Benjamin Haeffele
arXiv:2011.14859 (2020)
[arXiv] [code]
Neural Manifold Ordinary Differential Equations
Aaron Lou*, Derek Lim*, Isay Katsman*, Leo Huang*, Qingxuan Jiang, Ser-Nam Lim, and Christopher De Sa
NeurIPS (2020)
Also in ICML INNF Workshop, Spotlight (2020)
[arXiv] [code]
Expertise and Dynamics within Crowdsourced Musical Knowledge Curation: A Case Study of the Genius Platform
Derek Lim, and Austin R. Benson
International AAAI Conference on Web and Social Media, ICWSM (2021)
[arXiv] [code]
[Podcast] interview with Data Skeptic
\[HS(\rho_k(D_{2n})) = \Pi_{\frac{n}{\mathrm{gcd}(n,k)}} \cup \Pi_2\] \[HS(\rho(Q_8)) = \Pi_4\] Spectra of Convex Hulls of Matrix Groups
Eric Jankowski*, Charles R. Johnson*, and Derek Lim*
Linear Algebra and its Applications 593 (2020): 74-89
[arXiv] [doi]
The Doubly Stochastic Single Eigenvalue Problem: A Computational Approach
Amit Harlev*, Charles R. Johnson*, and Derek Lim*
Experimental Mathematics (2020)
[arXiv] [code] [doi]