| Emergence of invariance and disentanglement in deep representations A Achille, S Soatto The Journal of Machine Learning Research 19 (1), 1947-1980, 2018 | 454* | 2018 |
| Information Dropout: Learning optimal representations through noisy computation A Achille, S Soatto IEEE Transactions on Pattern Analysis and Machine Intelligence 40 (12), 2897 …, 2018 | 349 | 2018 |
| Task2vec: Task embedding for meta-learning A Achille, M Lam, R Tewari, A Ravichandran, S Maji, CC Fowlkes, ... Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 180 | 2019 |
| Critical Learning Periods in Deep Networks A Achille, M Rovere, S Soatto International Conference on Learning Representations, 2019 | 145* | 2019 |
| Life-long disentangled representation learning with cross-domain latent homologies A Achille, T Eccles, L Matthey, CP Burgess, N Watters, A Lerchner, ... Conference on Neural Information Processing Systems, 2018 | 102 | 2018 |
| Eternal sunshine of the spotless net: Selective forgetting in deep networks A Golatkar, A Achille, S Soatto Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 91 | 2020 |
| Structured Prediction as Translation between Augmented Natural Languages G Paolini, B Athiwaratkun, J Krone, J Ma, A Achille, R Anubhai, ... International Conference on Learning Representations, 2021 | 77 | 2021 |
| Time matters in regularizing deep networks: Weight decay and data augmentation affect early learning dynamics, matter little near convergence A Golatkar, A Achille, S Soatto Conference on Neural Information Processing Systems, 2019 | 63 | 2019 |
| Where is the information in a deep neural network? A Achille, G Paolini, S Soatto ArXiv Preprints, arXiv:1905.12213 1905 (12213), 1-13, 2019 | 48 | 2019 |
| Toward understanding catastrophic forgetting in continual learning CV Nguyen, A Achille, M Lam, T Hassner, V Mahadevan, S Soatto arXiv preprint arXiv:1908.01091, 2019 | 47 | 2019 |
| Forgetting Outside the Box: Scrubbing Deep Networks of Information Accessible from Input-Output Observations A Golatkar, A Achille, S Soatto European Conference on Computer Vision, 2020 | 45 | 2020 |
| Mixed-Privacy Forgetting in Deep Networks A Golatkar, A Achille, A Ravichandran, M Polito, S Soatto The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020 | 40 | 2020 |
| The information complexity of learning tasks, their structure and their distance A Achille, G Paolini, G Mbeng, S Soatto Information and Inference: A Journal of the IMA, 2019 | 33* | 2019 |
| Layouttransformer: Layout generation and completion with self-attention K Gupta, J Lazarow, A Achille, LS Davis, V Mahadevan, A Shrivastava Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 31* | 2021 |
| E46K-like α-synuclein mutants increase lipid interactions and disrupt membrane selectivity M Rovere, AE Powers, H Jiang, JC Pitino, L Fonseca-Ornelas, DS Patel, ... Journal of Biological Chemistry 294 (25), 9799-9812, 2019 | 29 | 2019 |
| Incremental Meta-Learning via Indirect Discriminant Alignment Q Liu, O Majumder, A Achille, A Ravichandran, R Bhotika, S Soatto European Conference on Computer Vision, 2020 | 25* | 2020 |
| A linearized framework and a new benchmark for model selection for fine-tuning A Deshpande, A Achille, A Ravichandran, H Li, L Zancato, C Fowlkes, ... arXiv preprint arXiv:2102.00084, 2021 | 18 | 2021 |
| Adversarial training reduces information and improves transferability M Terzi, A Achille, M Maggipinto, GA Susto AAAI 2021, 2020 | 15 | 2020 |
| A separation principle for control in the age of deep learning A Achille, S Soatto Annual Review of Control, Robotics, and Autonomous Systems 1, 287-307, 2018 | 14 | 2018 |
| LQF: Linear Quadratic Fine-Tuning A Achille, A Golatkar, A Ravichandran, M Polito, S Soatto The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020 | 12 | 2020 |
Stefano SoattoProfessor of Computer Science, UCLA; VP, AWSVerified email at ucla.edu
