Joshua Robinson

28 papers A* 12Journal 13Unranked 2
YearRankTypeTitle / Venue / Authors
2025 A* conf
Holographic Node Representations: Pre-training Task-Agnostic Node Embeddings.
ICLR
Beatrice Bevilacqua, Joshua Robinson, Jure Leskovec, Bruno Ribeiro
2025 A* conf
Zero-Shot Generalization of GNNs over Distinct Attribute Domains.
ICML
Yangyi Shen, Jincheng Zhou, Beatrice Bevilacqua, Joshua Robinson, Charilaos I. Kanatsoulis, Jure Leskovec, Bruno Ribeiro
2024 A* conf
On the Stability of Expressive Positional Encodings for Graphs.
ICLR
Yinan Huang, William Lu, Joshua Robinson, Yu Yang, Muhan Zhang, Stefanie Jegelka, Pan Li
2024 A* conf
Position: Relational Deep Learning - Graph Representation Learning on Relational Databases.
ICML
Matthias Fey, Weihua Hu, Kexin Huang, Jan Eric Lenssen, Rishabh Ranjan, Joshua Robinson, Rex Ying, Jiaxuan You, Jure Leskovec
2024 A* conf
RelBench: A Benchmark for Deep Learning on Relational Databases.
NeurIPS
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
2024 J jnl
RelBench: A Benchmark for Deep Learning on Relational Databases.
CoRR
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
2024 A* conf
Structuring Representation Geometry with Rotationally Equivariant Contrastive Learning.
ICLR
Sharut Gupta, Joshua Robinson, Derek Lim, Soledad Villar, Stefanie Jegelka
2023 A* conf
Expressive Sign Equivariant Networks for Spectral Geometric Learning.
NeurIPS
Derek Lim, Joshua Robinson, Stefanie Jegelka, Haggai Maron
2023 J jnl
Expressive Sign Equivariant Networks for Spectral Geometric Learning.
CoRR
Derek Lim, Joshua Robinson, Stefanie Jegelka, Haggai Maron
2023 — —
Modeling the Geometry of Neural Network Representation Spaces
Joshua Robinson
2023 J jnl
On the Stability of Expressive Positional Encodings for Graph Neural Networks.
CoRR
Yinan Huang, William Lu, Joshua Robinson, Yu Yang, Muhan Zhang, Stefanie Jegelka, Pan Li
2023 J jnl
Relational Deep Learning: Graph Representation Learning on Relational Databases.
CoRR
Matthias Fey, Weihua Hu, Kexin Huang, Jan Eric Lenssen, Rishabh Ranjan, Joshua Robinson, Rex Ying, Jiaxuan You, Jure Leskovec
2023 J jnl
Structuring Representation Geometry with Rotationally Equivariant Contrastive Learning.
CoRR
Sharut Gupta, Joshua Robinson, Derek Lim, Soledad Villar, Stefanie Jegelka
2023 — conf
The Second Learning on Graphs Conference: Preface.
LoG
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
2022 J jnl
A simple, efficient and scalable contrastive masked autoencoder for learning visual representations.
CoRR
Shlok Mishra, Joshua Robinson, Huiwen Chang, David Jacobs, Aaron Sarna, Aaron Maschinot, Dilip Krishnan
2022 A* conf
Neural Set Function Extensions: Learning with Discrete Functions in High Dimensions.
NeurIPS
Nikolaos Karalias, Joshua Robinson, Andreas Loukas, Stefanie Jegelka
2022 J jnl
Neural Set Function Extensions: Learning with Discrete Functions in High Dimensions.
CoRR
Nikolaos Karalias, Joshua Robinson, Andreas Loukas, Stefanie Jegelka
2022 J jnl
Sign and Basis Invariant Networks for Spectral Graph Representation Learning.
CoRR
Derek Lim, Joshua Robinson, Lingxiao Zhao, Tess E. Smidt, Suvrit Sra, Haggai Maron, Stefanie Jegelka
2022 — conf
The First Learning on Graphs Conference: Preface.
LoG
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
2021 A* conf
Can contrastive learning avoid shortcut solutions?
NeurIPS
Joshua Robinson, Li Sun, Ke Yu, Kayhan Batmanghelich, Stefanie Jegelka, Suvrit Sra
2021 J jnl
Can contrastive learning avoid shortcut solutions?
CoRR
Joshua Robinson, Li Sun, Ke Yu, Kayhan Batmanghelich, Stefanie Jegelka, Suvrit Sra
2020 J jnl
Contrastive Learning with Hard Negative Samples.
CoRR
Joshua Robinson, Ching-Yao Chuang, Suvrit Sra, Stefanie Jegelka
2020 A* conf
Debiased Contrastive Learning.
NeurIPS
Ching-Yao Chuang, Joshua Robinson, Yen-Chen Lin, Antonio Torralba, Stefanie Jegelka
2020 J jnl
Debiased Contrastive Learning.
CoRR
Ching-Yao Chuang, Joshua Robinson, Yen-Chen Lin, Antonio Torralba, Stefanie Jegelka
2020 A* conf
Strength from Weakness: Fast Learning Using Weak Supervision.
ICML
Joshua Robinson, Stefanie Jegelka, Suvrit Sra
2020 J jnl
Strength from Weakness: Fast Learning Using Weak Supervision.
CoRR
Joshua Robinson, Stefanie Jegelka, Suvrit Sra
2019 A* conf
Flexible Modeling of Diversity with Strongly Log-Concave Distributions.
NeurIPS
Joshua Robinson, Suvrit Sra, Stefanie Jegelka
2019 J jnl
Flexible Modeling of Diversity with Strongly Log-Concave Distributions.
CoRR
Joshua Robinson, Suvrit Sra, Stefanie Jegelka