Publications

This page is often out of date as it takes me a while to pick out pictures. My Google Scholar is always up to date.

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
Preprint
Publication year: 2022

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

Nikolaos Karalias*, Joshua Robinson*, Andreas Loukas, Stefanie Jegelka
NeurIPS
Publication year: 2022

Sign and basis invariant networks for spectral graph representations

Derek Lim*, Joshua Robinson*, Lingxiao Zhao, Tess Smidt, Suvrit Sra, Haggai Maron, Stefanie Jegelka
ICLR Spotlight
Publication year: 2023

Can contrastive learning avoid shortcut solutions?

Joshua Robinson, Li Sun, Ke Yu, Kayhan Batmanghelich, Stefanie Jegelka, Suvrit Sra
NeurIPS
Publication year: 2021

Contrastive learning with hard negative samples

Joshua Robinson, Ching-Yao Chuang, Suvrit Sra, Stefanie Jegelka
ICLR
Publication year: 2021

Debiased contrastive learning

Ching-Yao Chuang, Joshua Robinson, Lin Yen-Chen, Antonio Torralba, Stefanie Jegelka
NeurIPS Spotlight
Publication year: 2020

Optimal batch variance with second-order marginals

Zelda Mariet, Joshua Robinson, Jamie Smith, Suvrit Sra, Stefanie Jegelka
ICML 2020 Workshop on Real World Experiment Design and Active Learning
Publication year: 2020

Strength from weakness: fast learning using weak supervision

Joshua Robinson, Stefanie Jegelka, Suvrit Sra
ICML
Publication year: 2020

Flexible modeling of diversity with strongly log-concave distributions

Joshua Robinson, Suvrit Sra, Stefanie Jegelka
NeurIPS
Publication year: 2019

Aggregation of Markov flows I: theory

Robert MacKay, Joshua Robinson
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
Publication year: 2018