| Scalable verified training for provably robust image classification S Gowal, KD Dvijotham, R Stanforth, R Bunel, C Qin, J Uesato, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 909* | 2019 |
| A unified view of piecewise linear neural network verification R Bunel, I Turkaslan, PHS Torr, P Kohli, MP Kumar NeurIPS, 2018 | 591* | 2018 |
| Contrastive Training for Improved Out-of-Distribution Detection AG Roy, A Karthikesalingam, J Winkens, J Ledsam, O Ronneberger, ... | 320* | 2020 |
| Branch and bound for piecewise linear neural network verification R Bunel, J Lu, I Turkaslan, PHS Torr, P Kohli, MP Kumar Journal of Machine Learning Research 21 (42), 1-39, 2020 | 311 | 2020 |
| Leveraging grammar and reinforcement learning for neural program synthesis R Bunel, M Hausknecht, J Devlin, R Singh, P Kohli International Conference on Learning Representations (ICLR), 2018 | 275 | 2018 |
| Scalable watermarking for identifying large language model outputs S Dathathri, A See, S Ghaisas, PS Huang, R McAdam, J Welbl, V Bachani, ... Nature 634 (8035), 818-823, 2024 | 204 | 2024 |
| Enabling certification of verification-agnostic networks via memory-efficient semidefinite programming S Dathathri, K Dvijotham, A Kurakin, A Raghunathan, J Uesato, R Bunel, ... NeurIPS, 2020 | 145 | 2020 |
| Neural program meta-induction J Devlin, R Bunel, R Singh, M Hausknecht, P Kohli NeurIPS, 2017 | 99 | 2017 |
| Improved branch and bound for neural network verification via lagrangian decomposition A De Palma, R Bunel, A Desmaison, K Dvijotham, P Kohli, PHS Torr, ... arXiv preprint arXiv:2104.06718, 2021 | 95 | 2021 |
| Imagen 3 J Baldridge, J Bauer, M Bhutani, N Brichtova, A Bunner, L Castrejon, ... arXiv preprint arXiv:2408.07009, 2024 | 90 | 2024 |
| Scaling the Convex Barrier With Active Sets A De Palma, HS Behl, R Bunel, PHS Torr, MP Kumar ICLR, 2021 | 88 | 2021 |
| Lagrangian decomposition for neural network verification MPK Rudy Bunel, Alessandro De Palma, Alban Desmaison, Krishnamurthy ... Conference on Uncertainty in Artificial Intelligence, 2020 | 73* | 2020 |
| Adaptive neural compilation R Bunel, A Desmaison, P Kohli, PHS Torr, MP Kumar NeurIPS, 2016 | 61 | 2016 |
| Verification of non-linear specifications for neural networks C Qin, B O'Donoghue, R Bunel, R Stanforth, S Gowal, J Uesato, ... International Conference on Learning Representation (ICLR), 2019 | 55 | 2019 |
| Learning to superoptimize programs R Bunel, A Desmaison, MP Kumar, PHS Torr, P Kohli International Conference on Learning Representations (ICLR), 2017 | 44 | 2017 |
| Efficient continuous relaxations for dense CRF A Desmaison, R Bunel, P Kohli, PHS Torr, MP Kumar European Conference on Computer Vision (ECCV), 818-833, 2016 | 37 | 2016 |
| Make sure you're unsure: A framework for verifying probabilistic specifications L Berrada, S Dathathri, K Dvijotham, R Stanforth, RR Bunel, J Uesato, ... Advances in Neural Information Processing Systems 34, 11136-11147, 2021 | 33* | 2021 |
| IBP regularization for verified adversarial robustness via branch-and-bound A De Palma, R Bunel, K Dvijotham, MP Kumar, R Stanforth arXiv preprint arXiv:2206.14772, 2022 | 26 | 2022 |
| Expressive losses for verified robustness via convex combinations A De Palma, R Bunel, K Dvijotham, MP Kumar, R Stanforth, A Lomuscio arXiv preprint arXiv:2305.13991, 2023 | 24 | 2023 |
| An efficient nonconvex reformulation of stagewise convex optimization problems R Bunel, O Hinder, S Bhojanapalli, K Dvijotham NeurIPS, 2020 | 24 | 2020 |
Pushmeet KohliVP of Science, Google DeepMindVerified email at google.com
