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ORCIDJoshua Robinson 0001
Person information
- affiliation: Massachusetts Institute of Technology, Cambridge, MA, USA
Other persons with the same name
- Joshua Robinson — disambiguation page
- Joshua Robinson 0002 — Narus, Inc., Sunnyvale, CA, USA (and 1 more)
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2020 – today
- 2024
[c13]Sharut Gupta, Joshua Robinson, Derek Lim, Soledad Villar, Stefanie Jegelka:
Structuring Representation Geometry with Rotationally Equivariant Contrastive Learning. ICLR 2024- [c12]Yinan Huang, William Lu, Joshua Robinson, Yu Yang, Muhan Zhang, Stefanie Jegelka, Pan Li:
On the Stability of Expressive Positional Encodings for Graphs. ICLR 2024 - [c11]Matthias Fey, Weihua Hu, Kexin Huang, Jan Eric Lenssen, Rishabh Ranjan, Joshua Robinson, Rex Ying, Jiaxuan You, Jure Leskovec:
Position: Relational Deep Learning - Graph Representation Learning on Relational Databases. ICML 2024 - [i13]Joshua Robinson, Rishabh Ranjan, Weihua Hu, Kexin Huang, Jiaqi Han, Alejandro Dobles, Matthias Fey, Jan Eric Lenssen, Yiwen Yuan, Zecheng Zhang, Xinwei He, Jure Leskovec:
RelBench: A Benchmark for Deep Learning on Relational Databases. CoRR abs/2407.20060 (2024) - 2023
- [b1]Joshua Robinson:
Modeling the Geometry of Neural Network Representation Spaces. MIT, USA, 2023 - [c10]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 - [c9]Soledad Villar, Benjamin Paul Chamberlain, Yuanqi Du, Hannes Stärk, Chaitanya K. Joshi, Andreea Deac, Iulia Duta, Joshua Robinson, Yanqiao Zhu, Kexin Huang, Michelle M. Li, Sofia Bourhim, Ilia Igashov, Alexandre Duval, Mathieu Alain, Dominique Beaini, Xinyu Yuan:
The Second Learning on Graphs Conference: Preface. LoG 2023: i-xix - [c8]Derek Lim, Joshua Robinson, Stefanie Jegelka, Haggai Maron:
Expressive Sign Equivariant Networks for Spectral Geometric Learning. NeurIPS 2023 - [i12]Sharut Gupta, Joshua Robinson, Derek Lim, Soledad Villar, Stefanie Jegelka:
Structuring Representation Geometry with Rotationally Equivariant Contrastive Learning. CoRR abs/2306.13924 (2023) - [i11]Yinan Huang, William Lu, Joshua Robinson, Yu Yang, Muhan Zhang, Stefanie Jegelka, Pan Li:
On the Stability of Expressive Positional Encodings for Graph Neural Networks. CoRR abs/2310.02579 (2023) - [i10]Derek Lim, Joshua Robinson, Stefanie Jegelka, Haggai Maron:
Expressive Sign Equivariant Networks for Spectral Geometric Learning. CoRR abs/2312.02339 (2023) - [i9]Matthias Fey, Weihua Hu, Kexin Huang, Jan Eric Lenssen, Rishabh Ranjan, Joshua Robinson, Rex Ying, Jiaxuan You, Jure Leskovec:
Relational Deep Learning: Graph Representation Learning on Relational Databases. CoRR abs/2312.04615 (2023) - 2022
- [c7]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 - [c6]Nikolaos Karalias, Joshua Robinson, Andreas Loukas, Stefanie Jegelka:
Neural Set Function Extensions: Learning with Discrete Functions in High Dimensions. NeurIPS 2022 - [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) - [i7]Nikolaos Karalias, Joshua Robinson, Andreas Loukas, Stefanie Jegelka:
Neural Set Function Extensions: Learning with Discrete Functions in High Dimensions. CoRR abs/2208.04055 (2022) - [i6]Shlok Mishra, Joshua Robinson, Huiwen Chang, David Jacobs, Aaron Sarna, Aaron Maschinot, Dilip Krishnan:
A simple, efficient and scalable contrastive masked autoencoder for learning visual representations. CoRR abs/2210.16870 (2022) - 2021
- [c5]Joshua David Robinson, Ching-Yao Chuang, Suvrit Sra, Stefanie Jegelka:
Contrastive Learning with Hard Negative Samples. ICLR 2021 - [c4]Joshua Robinson, Li Sun, Ke Yu, Kayhan Batmanghelich, Stefanie Jegelka, Suvrit Sra:
Can contrastive learning avoid shortcut solutions? NeurIPS 2021: 4974-4986 - [i5]Joshua Robinson, Li Sun, Ke Yu, Kayhan Batmanghelich, Stefanie Jegelka, Suvrit Sra:
Can contrastive learning avoid shortcut solutions? CoRR abs/2106.11230 (2021) - 2020
- [c3]Joshua Robinson, Stefanie Jegelka, Suvrit Sra:
Strength from Weakness: Fast Learning Using Weak Supervision. ICML 2020: 8127-8136 - [c2]Ching-Yao Chuang, Joshua Robinson, Yen-Chen Lin, Antonio Torralba, Stefanie Jegelka:
Debiased Contrastive Learning. NeurIPS 2020 - [i4]Joshua Robinson, Stefanie Jegelka, Suvrit Sra:
Strength from Weakness: Fast Learning Using Weak Supervision. CoRR abs/2002.08483 (2020) - [i3]Ching-Yao Chuang, Joshua Robinson, Yen-Chen Lin, Antonio Torralba, Stefanie Jegelka:
Debiased Contrastive Learning. CoRR abs/2007.00224 (2020) - [i2]Joshua Robinson, Ching-Yao Chuang, Suvrit Sra, Stefanie Jegelka:
Contrastive Learning with Hard Negative Samples. CoRR abs/2010.04592 (2020)
2010 – 2019
- 2019
- [c1]Joshua Robinson, Suvrit Sra, Stefanie Jegelka:
Flexible Modeling of Diversity with Strongly Log-Concave Distributions. NeurIPS 2019: 15199-15209 - [i1]Joshua Robinson, Suvrit Sra, Stefanie Jegelka:
Flexible Modeling of Diversity with Strongly Log-Concave Distributions. CoRR abs/1906.05413 (2019)
Coauthor Index
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