| 2022 | ICLR | FairCal: Fairness Calibration for Face Verification. | Tiago Salvador, Stephanie Cairns, Vikram Voleti, Noah Marshall, Adam M. Oberman |
| 2022 | ICPRAM | EuclidNets: Combining Hardware and Architecture Design for Efficient Training and Inference. | Mariana Oliveira Prazeres, Xinlin Li, Adam M. Oberman, Vahid Partovi Nia |
| 2020 | AISTATS | A Lyapunov analysis for accelerated gradient methods: from deterministic to stochastic case. | Maxime Laborde, Adam M. Oberman |
| 2020 | AISTATS | A principled approach for generating adversarial images under non-smooth dissimilarity metrics. | Aram-Alexandre Pooladian, Chris Finlay, Tim Hoheisel, Adam M. Oberman |
| 2020 | ICML | How to Train Your Neural ODE: the World of Jacobian and Kinetic Regularization. | Chris Finlay, Jrn-Henrik Jacobsen, Levon Nurbekyan, Adam M. Oberman |
| 2019 | ICCV | The LogBarrier Adversarial Attack: Making Effective Use of Decision Boundary Information. | Chris Finlay, Aram-Alexandre Pooladian, Adam M. Oberman |
| 2017 | ACSSC | Partial differential equations for training deep neural networks. | Pratik Chaudhari, Adam M. Oberman, Stanley J. Osher, Stefano Soatto, Guillaume Carlier |