| Adversarial autoencoders A Makhzani, J Shlens, N Jaitly, I Goodfellow, B Frey International Conference on Learning Representations (ICLR) 2016 Workshop, 2015 | 3680* | 2015 |
| Starcraft II: A new challenge for reinforcement learning O Vinyals, T Ewalds, S Bartunov, P Georgiev, AS Vezhnevets, M Yeo, ... arXiv preprint arXiv:1708.04782, 2017 | 1230 | 2017 |
| k-Sparse Autoencoders A Makhzani, B Frey International Conference on Learning Representations (ICLR) 2014, 2014 | 559* | 2014 |
| Winner-take-all autoencoders A Makhzani, BJ Frey Neural Information Processing Systems (NeurIPS) 2015, 2015 | 337 | 2015 |
| Variational model inversion attacks KC Wang, Y Fu, K Li, A Khisti, R Zemel, A Makhzani Neural Information Processing Systems (NeurIPS) 2021, 2021 | 137 | 2021 |
| Pixelgan autoencoders A Makhzani, BJ Frey Neural Information Processing Systems (NeurIPS) 2017, 2017 | 132 | 2017 |
| Action Matching: Learning Stochastic Dynamics from Samples K Neklyudov, R Brekelmans, D Severo, A Makhzani International Conference on Machine Learning (ICML) 2023, 2023 | 52 | 2023 |
| A winner-take-all method for training sparse convolutional autoencoders A Makhzani, B Frey NIPS deep learning workshop, 2014 | 45 | 2014 |
| Improving lossless compression rates via monte carlo bits-back coding Y Ruan, K Ullrich, DS Severo, J Townsend, A Khisti, A Doucet, ... International Conference on Machine Learning (ICML) 2021 (Long Oral Talk), 2021 | 32 | 2021 |
| Implicit autoencoders A Makhzani arXiv preprint arXiv:1805.09804, 2018 | 31 | 2018 |
| Evaluating Lossy Compression Rates of Deep Generative Models S Huang, A Makhzani, Y Cao, R Grosse International Conference on Machine Learning (ICML) 2019, 2019 | 30 | 2019 |
| Probabilistic Inference in Language Models via Twisted Sequential Monte Carlo S Zhao, R Brekelmans, A Makhzani, R Grosse International Conference on Machine Learning (ICML) 2024 (Best Paper Award), 2024 | 27 | 2024 |
| Unsupervised representation learning with autoencoders A Makhzani PhD Thesis, University of Toronto (Canada) 2018, 2018 | 20 | 2018 |
| A computational framework for solving Wasserstein Lagrangian flows K Neklyudov, R Brekelmans, A Tong, L Atanackovic, Q Liu, A Makhzani International Conference on Machine Learning (ICML) 2024, 2024 | 16 | 2024 |
| Compressing Multisets with Large Alphabets using Bits-Back Coding D Severo, J Townsend, A Khisti, A Makhzani, K Ullrich IEEE Journal on Selected Areas in Information Theory (Special Issue on …, 2022 | 15* | 2022 |
| Improving mutual information estimation with annealed and energy-based bounds R Brekelmans, S Huang, M Ghassemi, GV Steeg, R Grosse, A Makhzani International Conference on Learning Representations (ICLR) 2022, 2022 | 15 | 2022 |
| Reconstruction of jointly sparse signals using iterative hard thresholding A Makhzani, S Valaee IEEE International Conference on Communications (ICC) 2012, 2012 | 15 | 2012 |
| Wasserstein Quantum Monte Carlo: A Novel Approach for Solving the Quantum Many-Body Schrödinger Equation K Neklyudov, J Nys, L Thiede, J Carrasquilla, Q Liu, M Welling, ... Neural Information Processing Systems (NeurIPS) 2023 (Spotlight Talk), 2023 | 12 | 2023 |
| Distributed spectrum sensing in cognitive radios via graphical models A Makhzani, S Valaee IEEE International Workshop on Computational Advances in Multi-Sensor …, 2013 | 12 | 2013 |
| Can We Remove the Square-Root in Adaptive Gradient Methods? A Second-Order Perspective W Lin, F Dangel, R Eschenhagen, J Bae, RE Turner, A Makhzani International Conference on Machine Learning (ICML) 2024, 2024 | 11 | 2024 |
Brendan FreyFounder & CEO, Deep Genomics; Co-Founder, Vector Institute; Professor, University of Torontopsi.toronto.edu의 이메일 확인됨
