| Towards verifying robustness of neural networks against a family of semantic perturbations J Mohapatra, TW Weng, PY Chen, S Liu, L Daniel Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 91* | 2020 |
| Higher-order certification for randomized smoothing J Mohapatra, CY Ko, TW Weng, PY Chen, S Liu, L Daniel Advances in Neural Information Processing Systems 33, 4501-4511, 2020 | 36 | 2020 |
| Hidden cost of randomized smoothing J Mohapatra, CY Ko, L Weng, PY Chen, S Liu, L Daniel International Conference on Artificial Intelligence and Statistics, 4033-4041, 2021 | 31* | 2021 |
| Revisiting contrastive learning through the lens of neighborhood component analysis: an integrated framework CY Ko, J Mohapatra, S Liu, PY Chen, L Daniel, L Weng International Conference on Machine Learning, 11387-11412, 2022 | 12 | 2022 |
| Optimal gossip algorithms for exact and approximate quantile computations B Haeupler, J Mohapatra, HH Su Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing …, 2018 | 12 | 2018 |
| Synbench: Task-agnostic benchmarking of pretrained representations using synthetic data CY Ko, PY Chen, J Mohapatra, P Das, L Daniel arXiv preprint arXiv:2210.02989, 2022 | 3 | 2022 |
| SynBench: Evaluating Pretrained Representations for Image Classification using Synthetic Data CY Ko, PY Chen, P Das, J Mohapatra, L Daniel | | 2023 |
| Generalizing Robustness Verification for Machine Learning J Mohapatra Massachusetts Institute of Technology, 2021 | | 2021 |
| Hessian Reparametrization for Coarse-grained Energy Minimization N Dehmamy, C Both, J Mohapatra, S Das, T Jaakkola ICLR 2024 Workshop on AI4DifferentialEquations In Science, 0 | | |
