Joshua Robinson

According to our database, Joshua Robinson authored at least 13 papers between 2019 and 2023.

Collaborative distances:

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

2023

Relational Deep Learning: Graph Representation Learning on Relational Databases.

Matthias Fey, Weihua Hu, Kexin Huang, Jan Eric Lenssen, Rishabh Ranjan, Joshua Robinson, Rex Ying, Jiaxuan You, Jure Leskovec

CoRR, 2023

On the Stability of Expressive Positional Encodings for Graph Neural Networks.

Yinan Huang, William Lu, Joshua Robinson, Yu Yang, Muhan Zhang, Stefanie Jegelka, Pan Li

CoRR, 2023

Structuring Representation Geometry with Rotationally Equivariant Contrastive Learning.

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

CoRR, 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

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

2022

A simple, efficient and scalable contrastive masked autoencoder for learning visual representations.

Shlok Mishra, Joshua Robinson, Huiwen Chang, David Jacobs, Aaron Sarna, Aaron Maschinot, Dilip Krishnan

CoRR, 2022

Neural Set Function Extensions: Learning with Discrete Functions in High Dimensions.

Nikolaos Karalias, Joshua Robinson, Andreas Loukas, Stefanie Jegelka

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 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

2021

Can contrastive learning avoid shortcut solutions?

Joshua Robinson, Li Sun, Ke Yu, Kayhan Batmanghelich, Stefanie Jegelka, Suvrit Sra

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

Contrastive Learning with Hard Negative Samples.

Joshua David Robinson, Ching-Yao Chuang, Suvrit Sra, Stefanie Jegelka

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Debiased Contrastive Learning.

Ching-Yao Chuang, Joshua Robinson, Yen-Chen Lin, Antonio Torralba, Stefanie Jegelka

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

Strength from Weakness: Fast Learning Using Weak Supervision.

Joshua Robinson, Stefanie Jegelka, Suvrit Sra

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Flexible Modeling of Diversity with Strongly Log-Concave Distributions.

Joshua Robinson, Suvrit Sra, Stefanie Jegelka

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019