Papers

Research Papers

* Denotes equal contribution or alphabetical authorship.

	The Empirical Impact of Neural Parameter Symmetries, or Lack Thereof Derek Lim, Moe Putterman, Robin Walters, Haggai Maron, Stefanie Jegelka arXiv:2405.20231 (2024) [arXiv]
	Graph Metanetworks for Processing Diverse Neural Architectures Derek Lim, Haggai Maron, Marc T. Law, Jonathan Lorraine, James Lucas ICLR, Spotlight (2024) [arXiv]
	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) [pdf]
	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) [arXiv]
	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]} [arXiv]
	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]

	The Empirical Impact of Neural Parameter Symmetries, or Lack Thereof Derek Lim, Moe Putterman, Robin Walters, Haggai Maron, Stefanie Jegelka arXiv:2405.20231 (2024) [arXiv]
	Graph Metanetworks for Processing Diverse Neural Architectures Derek Lim, Haggai Maron, Marc T. Law, Jonathan Lorraine, James Lucas ICLR, Spotlight (2024) [arXiv]
	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) [pdf]
	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) [arXiv]
	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]} [arXiv]
	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]