| Counterfactuals uncover the modular structure of deep generative models M Besserve, A Mehrjou, R Sun, B Schölkopf International Conference on Learning Representations 2020 (ICLR), 2018 | 113 | 2018 |
| Diffusion models for video prediction and infilling T Höppe, A Mehrjou, S Bauer, D Nielsen, A Dittadi Transactions on Machine Learning Research (TMLR), 2022 | 109 | 2022 |
| Dual instrumental variable regression K Muandet, A Mehrjou, SK Lee, A Raj Advances in Neural Information Processing Systems (NeurIPS) 33, 2710-2721, 2020 | 103 | 2020 |
| The Incomplete Rosetta Stone problem: Identifiability results for Multi-view Nonlinear ICA L Gresele*, PK Rubenstein*, A Mehrjou, F Locatello, B Schölkopf Uncertainty in Artificial Intelligence 2019 (UAI), 2019 | 92 | 2019 |
| Fidelity-weighted learning M Dehghani, A Mehrjou, S Gouws, J Kamps, B Schölkopf International Conference on Learning Representations 2018 (ICLR), 2017 | 80 | 2017 |
| Deep energy estimator networks S Saremi*, A Mehrjou*, B Schölkopf, A Hyvärinen arXiv preprint arXiv:1805.08306, 2018 | 77 | 2018 |
| Causal Curiosity: RL Agents Discovering Self-supervised Experiments for Causal Representation Learning SA Sontakke, A Mehrjou, L Itti, B Schölkopf International Conference on Machine Learning 2021 (ICML), 2020 | 70 | 2020 |
| Real-time prediction of COVID-19 related mortality using electronic health records P Schwab, A Mehrjou, S Parbhoo, LA Celi, J Hetzel, M Hofer, B Schölkopf, ... Nature Communications 12 (1), 1-16, 2021 | 67 | 2021 |
| Improved Bayesian information criterion for mixture model selection A Mehrjou, R Hosseini, BN Araabi Pattern Recognition Letters 69, 22-27, 2016 | 60 | 2016 |
| Automatic malaria diagnosis system A Mehrjou, T Abbasian, M Izadi 2013 First RSI/ISM International Conference on Robotics and Mechatronics …, 2013 | 43 | 2013 |
| Diffusion-Based Representation Learning K Abstreiter, S Mittal, S Bauer, B Schölkopf, A Mehrjou International Conference on Machine Learning 2023 (ICML), 2021 | 33 | 2021 |
| Tempered adversarial networks MSM Sajjadi, G Parascandolo, A Mehrjou, B Schölkopf International Conference on Machine Learning 2018 (ICML), 2018 | 32 | 2018 |
| Causalbench: A large-scale benchmark for network inference from single-cell perturbation data M Chevalley, Y Roohani, A Mehrjou, J Leskovec, P Schwab arXiv preprint arXiv:2210.17283, 2022 | 26 | 2022 |
| GeneDisco: A Benchmark for Experimental Design in Drug Discovery A Mehrjou, A Soleymani, A Jesson, P Notin, Y Gal, S Bauer, P Schwab International Conference on Learning Representations 2022 (ICLR), 2021 | 19 | 2021 |
| Nonstationary GANs: Analysis as Nonautonomous Dynamical Systems A Mehrjou, B Schölkopf ICML Workshop on Theoretical Foundations and Applications of Deep Generative …, 2018 | 17* | 2018 |
| Diffusion Based Representation Learning S Mittal, K Abstreiter, S Bauer, B Schölkopf, A Mehrjou International Conference on Machine Learning 2023 (ICML), 2023 | 16 | 2023 |
| Neural Lyapunov Redesign A Mehrjou, M Ghavamzadeh, B Schölkopf Learning for Dynamics and Control 2021 (L4DC), 2021 | 14 | 2021 |
| Fed-cd: Federated causal discovery from interventional and observational data A Abyaneh, N Scherrer, P Schwab, S Bauer, B Schölkopf, A Mehrjou arXiv preprint arXiv:2211.03846, 2022 | 8 | 2022 |
| From points to functions: Infinite-dimensional representations in diffusion models S Mittal, G Lajoie, S Bauer, A Mehrjou arXiv preprint arXiv:2210.13774, 2022 | 8 | 2022 |
| DiscoBAX-Discovery of optimal intervention sets in genomic experiment design C Lyle*, A Mehrjou*, P Notin*, A Jesson, S Bauer, Y Gal, P Schwab International Conference on Machine Learning 2023 (ICML), 2023 | 7 | 2023 |
Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems & ELLIS Institute Tübingen; Professor at ETHEmail verificata su tuebingen.mpg.de