| The DeepMind JAX Ecosystem I Babuschkin, K Baumli, A Bell, S Bhupatiraju, J Bruce, P Buchlovsky, ... URL http://github. com/deepmind 24, 25, 2020 | 70* | 2020 |
| Subset selection with shrinkage: Sparse linear modeling when the SNR is low R Mazumder, P Radchenko, A Dedieu Operations Research 71 (1), 129-147, 2023 | 66 | 2023 |
| Clone-structured graph representations enable flexible learning and vicarious evaluation of cognitive maps D George, RV Rikhye, N Gothoskar, JS Guntupalli, A Dedieu, ... Nature communications 12 (1), 2392, 2021 | 44* | 2021 |
| Learning sparse classifiers: Continuous and mixed integer optimization perspectives A Dedieu, H Hazimeh, R Mazumder Journal of Machine Learning Research 22 (2021), 2021 | 31 | 2021 |
| Learning higher-order sequential structure with cloned HMMs A Dedieu, N Gothoskar, S Swingle, W Lehrach, M Lázaro-Gredilla, ... arXiv preprint arXiv:1905.00507, 2019 | 11 | 2019 |
| Deep reinforcement learning for 2048 A Dedieu, J Amar | 9 | 2017 |
| Query Training: Learning a Worse Model to Infer Better Marginals in Undirected Graphical Models with Hidden Variables M Lázaro-Gredilla, W Lehrach, N Gothoskar, G Zhou, A Dedieu, D George Proceedings of the AAAI Conference on Artificial Intelligence 35 (9), 8252-8260, 2021 | 7* | 2021 |
| Solving L1-regularized SVMs and related linear programs: Revisiting the effectiveness of Column and Constraint Generation A Dedieu, R Mazumder, H Wang Journal of Machine Learning Research 23 (164), 1-41, 2022 | 5* | 2022 |
| A detailed mathematical theory of thalamic and cortical microcircuits based on inference in a generative vision model D George, M Lazaro-Gredilla, W Lehrach, A Dedieu, G Zhou Biorxiv, 2020.09. 09.290601, 2020 | 5 | 2020 |
| Improved error rates for sparse (group) learning with Lipschitz loss functions A Dedieu arXiv preprint arXiv:1910.08880, 2019 | 4* | 2019 |
| Error bounds for sparse classifiers in high-dimensions A Dedieu The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 4 | 2019 |
| PGMax: Factor Graphs for Discrete Probabilistic Graphical Models and Loopy Belief Propagation in JAX G Zhou, N Kumar, A Dedieu, M Lázaro-Gredilla, S Kushagra, D George arXiv preprint arXiv:2202.04110, 2022 | 3 | 2022 |
| Learning attention-controllable border-ownership for objectness inference and binding A Dedieu, RV Rikhye, M Lázaro-Gredilla, D George bioRxiv, 2020.12. 31.424926, 2021 | 3 | 2021 |
| Perturb-and-max-product: Sampling and learning in discrete energy-based models M Lazaro-Gredilla, A Dedieu, D George Advances in Neural Information Processing Systems 34, 928-940, 2021 | 2 | 2021 |
| An error bound for Lasso and Group Lasso in high dimensions A Dedieu arXiv preprint arXiv:1912.11398, 2019 | 2 | 2019 |
| Graphical Models with Attention for Context-Specific Independence and an Application to Perceptual Grouping G Zhou, W Lehrach, A Dedieu, M Lázaro-Gredilla, D George arXiv preprint arXiv:2112.03371, 2021 | 1 | 2021 |
| Sample-Efficient L0-L2 Constrained Structure Learning of Sparse Ising Models A Dedieu, M Lázaro-Gredilla, D George Proceedings of the AAAI Conference on Artificial Intelligence 35 (8), 7193-7200, 2021 | 1 | 2021 |
| Hierarchical Modeling and Shrinkage for User Session LengthPrediction in Media Streaming A Dedieu, R Mazumder, Z Zhu, H Vahabi Proceedings of the 27th ACM International Conference on Information and …, 2018 | 1 | 2018 |
| Learning noisy-OR Bayesian Networks with Max-Product Belief Propagation A Dedieu, G Zhou, D George, M Lazaro-Gredilla arXiv preprint arXiv:2302.00099, 2023 | | 2023 |
| Method and system for query training M Lazaro-Gredilla, W Lehrach, N Gothoskar, Z GuangYao, A Dedieu, ... US Patent App. 17/482,896, 2022 | | 2022 |
Dileep GeorgeResearch @DeepMind. Ex Co-founder at VicariousVerified email at vicarious.com
