| Stochastic activation pruning for robust adversarial defense GS Dhillon, K Azizzadenesheli, ZC Lipton, J Bernstein, J Kossaifi, ... International Conference on Learning Representations, 2018 | 258 | 2018 |
| signSGD: compressed optimisation for non-convex problems J Bernstein, YX Wang, K Azizzadenesheli, A Anandkumar International Conference on Machine Learning, 2018 | 238 | 2018 |
| signSGD with majority vote is communication efficient and fault tolerant J Bernstein, J Zhao, K Azizzadenesheli, A Anandkumar International Conference on Learning Representations, 2019 | 40 | 2019 |
| Markov transitions between attractor states in a recurrent neural network J Bernstein, I Dasgupta, D Rolnick, H Sompolinsky AAAI Spring Symposium Series, 2017 | 5 | 2017 |
| On the distance between two neural networks and the stability of learning J Bernstein, A Vahdat, Y Yue, MY Liu Advances in Neural Information Processing Systems 33, 2020 | 3 | 2020 |
| Learning compositional functions via multiplicative weight updates J Bernstein, J Zhao, M Meister, MY Liu, A Anandkumar, Y Yue Advances in Neural Information Processing Systems 33, 2020 | 2 | 2020 |
| The neural sampling hypothesis in dynamic environments J Bernstein Part III project report, University of Cambridge, 2016 | | 2016 |
| Quantum walk frameworks and quantum speedup of Markov mixing J Bernstein SURF project report, Caltech, 2015 | | 2015 |
| Project Swarm: How technological advances are inspired by swarming animals J Bernstein Extended project report, Manchester Grammar School, 2011 | | 2011 |
