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2020 – today
- 2023
[i9]Omri Puny, Derek Lim, Bobak Toussi Kiani, Haggai Maron, Yaron Lipman:
Equivariant Polynomials for Graph Neural Networks. CoRR abs/2302.11556 (2023)- 2022
- [j1]Amit Harlev, Charles R. Johnson, Derek Lim
:
The Doubly Stochastic Single Eigenvalue Problem: A Computational Approach. Exp. Math. 31(3): 936-945 (2022) - [c7]Beatrice Bevilacqua, Fabrizio Frasca, Derek Lim, Balasubramaniam Srinivasan, Chen Cai, Gopinath Balamurugan, Michael M. Bronstein, Haggai Maron:
Equivariant Subgraph Aggregation Networks. ICLR 2022 - [c6]Tianjiao Ding, Derek Lim, René Vidal, Benjamin D. Haeffele:
Understanding Doubly Stochastic Clustering. ICML 2022: 5153-5165 - [c5]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: i-xxiii - [i8]Derek Lim, Joshua Robinson, Lingxiao Zhao, Tess E. Smidt, Suvrit Sra, Haggai Maron, Stefanie Jegelka:
Sign and Basis Invariant Networks for Spectral Graph Representation Learning. CoRR abs/2202.13013 (2022) - 2021
- [c4]Derek Lim, Austin R. Benson:
Expertise and Dynamics within Crowdsourced Musical Knowledge Curation: A Case Study of the Genius Platform. ICWSM 2021: 373-384 - [c3]Isay Katsman, Aaron Lou, Derek Lim, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa:
Equivariant Manifold Flows. NeurIPS 2021: 10600-10612 - [c2]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: 20887-20902 - [i7]Derek Lim, Xiuyu Li, Felix Hohne, Ser-Nam Lim:
New Benchmarks for Learning on Non-Homophilous Graphs. CoRR abs/2104.01404 (2021) - [i6]Isay Katsman, Aaron Lou, Derek Lim, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa:
Equivariant Manifold Flows. CoRR abs/2107.08596 (2021) - [i5]Beatrice Bevilacqua, Fabrizio Frasca, Derek Lim, Balasubramaniam Srinivasan, Chen Cai, Gopinath Balamurugan, Michael M. Bronstein, Haggai Maron:
Equivariant Subgraph Aggregation Networks. CoRR abs/2110.02910 (2021) - [i4]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 abs/2110.14446 (2021) - 2020
- [c1]Aaron Lou, Derek Lim, Isay Katsman, Leo Huang, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa:
Neural Manifold Ordinary Differential Equations. NeurIPS 2020 - [i3]Derek Lim, Austin R. Benson:
Expertise and Dynamics within Crowdsourced Musical Knowledge Curation: A Case Study of the Genius Platform. CoRR abs/2006.08108 (2020) - [i2]Aaron Lou, Derek Lim, Isay Katsman, Leo Huang, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa:
Neural Manifold Ordinary Differential Equations. CoRR abs/2006.10254 (2020) - [i1]Derek Lim, René Vidal, Benjamin D. Haeffele:
Doubly Stochastic Subspace Clustering. CoRR abs/2011.14859 (2020)
Coauthor Index
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