| A Closer Look at Memorization in Deep Networks D Arpit*, S Jastrzebski*, N Ballas*, D Krueger*, E Bengio, MS Kanwal, ... International Conference on Machine Learning 2017, 2017 | 384* | 2017 |
| Three factors influencing minima in SGD S Jastrzebski*, Z Kenton*, D Arpit, N Ballas, A Fischer, Y Bengio, ... International Conference on Artificial Neural Networks 2018; International …, 2017 | 148 | 2017 |
| Parameter-Efficient Transfer Learning for NLP N Houlsby, A Giurgiu*, S Jastrzebski*, B Morrone, Q Laroussilhe, ... International Conference on Machine Learning (ICML) 2019, 2019 | 52 | 2019 |
| Residual connections encourage iterative inference S Jastrzebski*, D Arpit*, N Ballas, V Verma, T Che, Y Bengio International Conference on Learning Algorithms (ICLR) 2018, 2017 | 47 | 2017 |
| How to evaluate word embeddings? On importance of data efficiency and simple supervised tasks S Jastrzebski, D Leśniak, WM Czarnecki arXiv preprint arXiv:1702.02170, 2017 | 44 | 2017 |
| Learning to SMILE(S) S Jastrzebski, D Lesniak, WM Czarnecki International Conference on Learning Representation 2016 (Workshop track), 2016 | 44* | 2016 |
| Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening N Wu, J Phang, J Park, Y Shen, Z Huang, M Zorin, S Jastrzebski, T Févry, ... | 42 | 2019 |
| Learning to Compute Word Embeddings on the Fly D Bahdanau, T Bosc*, S Jastrzebski*, E Grefenstette, P Vincent, Y Bengio Montreal AI Symposium 2017, 2017 | 41 | 2017 |
| On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length S Jastrzębski, Z Kenton, N Ballas, A Fischer, Y Bengio, A Storkey International Conference on Learning Algorithms (ICLR) 2019, 2019 | 27* | 2019 |
| Osprey: Hyperparameter optimization for machine learning R McGibbon, C Hernández, M Harrigan, S Kearnes, M Sultan, ... Journal of Open Source Software 1 (5), 34, 2016 | 26 | 2016 |
| Cramer-Wold AutoEncoder J Tabor, S Knop, P Spurek, I Podolak, M Mazur, S Jastrzebski JMLR 8/2020 (accepted), 2018 | 16* | 2018 |
| Stiffness: A new perspective on generalization in neural networks S Fort, PK Nowak, S Jastrzebski, S Narayanan arXiv preprint arXiv:1901.09491, 2019 | 15 | 2019 |
| Evolutionary-Neural Hybrid Agents for Architecture Search K Maziarz, A Khorlin, Q de Laroussilhe, S Jastrzebski, T Mingxing, ... arXiv preprint arXiv:1811.09828, 2018 | 14* | 2018 |
| Dynamical Isometry is Achieved in Residual Networks in a Universal Way for any Activation Function W Tarnowski, P Warchoł, S Jastrzebski, J Tabor, M Nowak AISTATS 2019, 2018 | 11 | 2018 |
| Large Scale Structure of Neural Network Loss Landscapes S Fort, S Jastrzebski NeurIPS 2019, 2019 | 9 | 2019 |
| Commonsense mining as knowledge base completion? A study on the impact of novelty S Jastrzebski, D Bahdanau, S Hosseini, M Noukhovitch, Y Bengio, ... New Forms of Generalization in Deep Learning and Natural Language Processing …, 2018 | 8 | 2018 |
| The Break-Even Point on Optimization Trajectories of Deep Neural Networks S Jastrzebski, M Szymczak, S Fort, D Arpit, J Tabor, K Cho, K Geras International Conference on Learning Algorithms (ICLR) 2020, 2020 | 7 | 2020 |
| Density Invariant Detection of Osteoporosis Using Growing Neural Gas IT Podolak, SK Jastrzebski Proceedings of the 8th International Conference on Computer Recognition …, 2013 | 5 | 2013 |
| Quo vadis G Protein-Coupled Receptor ligands? A tool for analysis of the emergence of new groups of compounds over time AJB Damian Lesniak, Stanislaw Jastrzebski, Sabina Podlewska, Wojciech M ... Bioorganic & Medicinal Chemistry Letters, 2016 | 4* | 2016 |
| Three-dimensional descriptors for aminergic GPCRs: dependence on docking conformation and crystal structure S Jastrzebski, I Sieradzki, D Leśniak, J Tabor, AJ Bojarski, S Podlewska Molecular Diversity, 1-11, 2018 | 2 | 2018 |
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARVerified email at umontreal.ca
