| Hierarchical image classification using entailment cone embeddings A Dhall, A Makarova, O Ganea, D Pavllo, M Greeff, A Krause Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 46 | 2020 |
| Mixed-variable Bayesian optimization E Daxberger, A Makarova, M Turchetta, A Krause International Joint Conference on Artificial Intelligence (IJCAI), 2019 | 43 | 2019 |
| Risk-averse Heteroscedastic Bayesian Optimization A Makarova, I Usmanova, I Bogunovic, A Krause Neural Information Processing Systems (NeurIPS) 35, 2021 | 32 | 2021 |
| Automatic Termination for Hyperparameter Optimization A Makarova, H Shen, V Perrone, A Klein, JB Faddoul, A Krause, ... International Conference on Automated Machine Learning (AutoML-Conf), 2021 | 22 | 2021 |
| Model-based Causal Bayesian Optimization S Sussex, A Makarova, A Krause International Conference on Learning Representations (ICLR) 2023, 2022 | 14 | 2022 |
| Overfitting in Bayesian Optimization: an empirical study and early-stopping solution A Makarova, H Shen, V Perrone, A Klein, JB Faddoul, A Krause, ... Proceedings of International Conference on Learning Representations Workshops, 2021 | 13 | 2021 |
| Cherry-Picking gradients: learning low-rank embeddings of visual data via differentiable cross-approximation M Usvyatsov, A Makarova, R Ballester-Ripoll, M Rakhuba, A Krause, ... International Conference on Computer Vision (ICCV), 2021 | 6 | 2021 |
| Safe Risk-averse Bayesian Optimization for Controller Tuning C Koenig, M Ozols, A Makarova, EC Balta, A Krause, A Rupenyan International Conference on Robotics and Automation (ICRA) 2024, 2023 | 3 | 2023 |
| Calibration of agent based transport simulations with multi-fidelity Bayesian optimization M Turchetta, A Makarova, S Beyeler, A Krause 18th Swiss Transport Research Conference (STRC 2018), 2018 | 3 | 2018 |
| Adversarial Causal Bayesian Optimization S Sussex, PG Sessa, A Makarova, A Krause International Conference on Learning Representations (ICLR) 2024, 2023 | 1 | 2023 |
| Bayesian Optimization in the wild: Risk-averse and Computationally-effective Decision-making A Makarova ETH Zurich, 2023 | | 2023 |
| Shifted Convolutions for Speeding up of Convolutional networks A Makarova, V Lebedev, V Lempitsky 11th Russian Summer School in Information Retrieval, 2017 | | 2017 |
Andreas KrauseProfessor of Computer Science, ETH ZurichVerified email at inf.ethz.ch
