| A comprehensive assessment of regional variation in the impact of head micromovements on functional connectomics CG Yan, B Cheung, C Kelly, S Colcombe, RC Craddock, A Di Martino, ... Neuroimage 76, 183-201, 2013 | 1436 | 2013 |
| The NKI-Rockland Sample: A Model for Accelerating the Pace of Discovery Science in Psychiatry KB Nooner, S Colcombe, R Tobe, M Mennes, M Benedict, A Moreno, ... Frontiers in Neuroscience 6, 152, 0 | 797 | |
| Adversarial examples that fool both computer vision and time-limited humans G Elsayed, S Shankar, B Cheung, N Papernot, A Kurakin, I Goodfellow, ... Advances in neural information processing systems 31, 2018 | 366 | 2018 |
| Towards automated analysis of connectomes: The configurable pipeline for the analysis of connectomes (c-pac) C Craddock, S Sikka, B Cheung, R Khanuja, SS Ghosh, C Yan, Q Li, ... Front Neuroinform 42 (10.3389), 2013 | 271 | 2013 |
| Discovering hidden factors of variation in deep networks B Cheung, JA Livezey, AK Bansal, BA Olshausen arXiv preprint arXiv:1412.6583, 2014 | 225 | 2014 |
| Meta-learning update rules for unsupervised representation learning L Metz, N Maheswaranathan, B Cheung, J Sohl-Dickstein ICLR, 2018 | 182* | 2018 |
| Superposition of many models into one B Cheung, A Terekhov, Y Chen, P Agrawal, B Olshausen Advances in neural information processing systems 32, 2019 | 125 | 2019 |
| Equivariant contrastive learning R Dangovski, L Jing, C Loh, S Han, A Srivastava, B Cheung, P Agrawal, ... arXiv preprint arXiv:2111.00899, 2021 | 114 | 2021 |
| The low-rank simplicity bias in deep networks M Huh, H Mobahi, R Zhang, B Cheung, P Agrawal, P Isola arXiv preprint arXiv:2103.10427, 2021 | 96 | 2021 |
| Cautious adaptation for reinforcement learning in safety-critical settings J Zhang, B Cheung, C Finn, S Levine, D Jayaraman International Conference on Machine Learning, 11055-11065, 2020 | 62 | 2020 |
| Convolutional neural networks applied to human face classification B Cheung 2012 11th International Conference on Machine Learning and Applications 2 …, 2012 | 51 | 2012 |
| Emergence of foveal image sampling from learning to attend in visual scenes B Cheung, E Weiss, B Olshausen International Conference on Learning Representations, 2017 | 48 | 2017 |
| Towards automated analysis of connectomes: The configurable pipeline for the analysis of connectomes (c-pac) S Sikka, B Cheung, R Khanuja, S Ghosh, C Yan, Q Li, J Vogelstein, ... 5th INCF Congress of Neuroinformatics, Munich, Germany 10, 2014 | 43 | 2014 |
| The NKI-Rockland sample: a model for accelerating the pace of discovery science in psychiatry. Front. Neurosci. 6, 152 KB Nooner, SJ Colcombe, RH Tobe, M Mennes, MM Benedict, AL Moreno, ... | 33 | 2012 |
| Hybrid evolution of convolutional networks B Cheung, C Sable 2011 10th international conference on machine learning and applications and …, 2011 | 24 | 2011 |
| Hardware-Optimized Ziggurat Algorithm for High-Speed Gaussian Random Number Generators HM Edrees, B Cheung, MC Sandora, D Nummey, D Stefan International Conference on Engineering of Reconfigurable Systems …, 2009 | 24 | 2009 |
| Detecting stable individual differences in the functional organization of the human basal ganglia M Garcia-Garcia, A Nikolaidis, P Bellec, RC Craddock, B Cheung, ... Neuroimage 170, 68-82, 2018 | 21 | 2018 |
| A neural architecture for representing and reasoning about spatial relationships E Weiss, B Cheung, B Olshausen | 18 | 2016 |
| Straightening out the straight-through estimator: Overcoming optimization challenges in vector quantized networks M Huh, B Cheung, P Agrawal, P Isola International Conference on Machine Learning, 14096-14113, 2023 | 16 | 2023 |
| Word embedding visualization via dictionary learning J Zhang, Y Chen, B Cheung, BA Olshausen arXiv preprint arXiv:1910.03833, 2019 | 13 | 2019 |
Michael MilhamChild Mind Institute, Nathan Kline Institute在 childmind.org 的电子邮件经过验证
