| Pytorch: An imperative style, high-performance deep learning library A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ... Advances in neural information processing systems 32, 2019 | 15328 | 2019 |
| Automatic differentiation in pytorch A Paszke, S Gross, S Chintala, G Chanan, E Yang, Z DeVito, Z Lin, ... 31st Conference on Neural Information Processing Systems (NIPS 2017), 2017 | 9740 | 2017 |
| Advances in Neural Information Processing Systems 32 A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ... Curran Associates, Inc, 8024-8035, 2019 | 370 | 2019 |
| Learning disentangled representations with semi-supervised deep generative models B Paige, JW van de Meent, A Desmaison, N Goodman, P Kohli, F Wood, ... Advances in neural information processing systems 30, 2017 | 287 | 2017 |
| PyTorch: an imperative style A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ... High-Performance Deep Learning Library 12, 2019 | 191 | 2019 |
| Pytorch: An imperative style, high-performance deep learning library. arXiv 2019 A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ... arXiv preprint arXiv:1912.01703, 1912 | 112 | 1912 |
| Playing doom with slam-augmented deep reinforcement learning S Bhatti, A Desmaison, O Miksik, N Nardelli, N Siddharth, PHS Torr arXiv preprint arXiv:1612.00380, 2016 | 76 | 2016 |
| Adaptive neural compilation RR Bunel, A Desmaison, PK Mudigonda, P Kohli, P Torr Advances in Neural Information Processing Systems 29, 2016 | 46 | 2016 |
| Efficient continuous relaxations for dense CRF A Desmaison, R Bunel, P Kohli, PHS Torr, MP Kumar European conference on computer vision, 818-833, 2016 | 35 | 2016 |
| Learning to superoptimize programs R Bunel, A Desmaison, MP Kumar, PHS Torr, P Kohli International Conference on Learning Representations (ICLR), 2017 | 31 | 2017 |
| Lagrangian decomposition for neural network verification R Bunel, A De Palma, A Desmaison, K Dvijotham, P Kohli, P Torr, ... Conference on Uncertainty in Artificial Intelligence, 370-379, 2020 | 22 | 2020 |
| Efficient linear programming for dense CRFs T Ajanthan, A Desmaison, R Bunel, M Salzmann, PHS Torr, ... Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 20 | 2017 |
| Inducing interpretable representations with variational autoencoders N Siddharth, B Paige, A Desmaison, JW Van de Meent, F Wood, ... arXiv preprint arXiv:1611.07492, 2016 | 11 | 2016 |
| 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 | 9 | 2021 |
| Efficient relaxations for dense crfs with sparse higher-order potentials T Joy, A Desmaison, T Ajanthan, R Bunel, M Salzmann, P Kohli, PHS Torr, ... SIAM journal on imaging sciences 12 (1), 287-318, 2019 | 9 | 2019 |
| Learning disentangled representations in deep generative models N Siddharth, B Paige, A Desmaison, JW van de Meent, F Wood, ... | 3 | 2016 |
| Learning Disentangled Representations in Deep Generative Models.(2016) N Siddharth, B Paige, A Desmaison, JW van de Meent, F Wood, ... Google Scholar Google Scholar Digital Library Digital Library, 2016 | 2 | 2016 |
| Power consumption analysis of parallel algorithms on GPUs F Magoulès, AKC Ahamed, A Desmaison, JC Léchenet, F Mayer, ... 2014 IEEE Intl Conf on High Performance Computing and Communications, 2014 …, 2014 | 2 | 2014 |
| Fast and green computing with graphics processing units for solving sparse linear systems AKC Ahamed, A Desmaison, F Magoulès 2014 IEEE Intl Conf on High Performance Computing and Communications, 2014 …, 2014 | 2 | 2014 |
| Fast and Green Computing with Graphics Processing Units for solving Sparse Linear Systems AK Cheik Ahamed, A Desmaison, F Magoules arXiv e-prints, arXiv: 2112.10823, 2021 | | 2021 |
