| 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 | 1007 | 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 | 478 | |
| Adversarial examples that fool both computer vision and time-limited humans GF Elsayed, S Shankar, B Cheung, N Papernot, A Kurakin, I Goodfellow, ... arXiv preprint arXiv:1802.08195, 2018 | 202 | 2018 |
| Discovering hidden factors of variation in deep networks B Cheung, JA Livezey, AK Bansal, BA Olshausen arXiv preprint arXiv:1412.6583, 2014 | 163 | 2014 |
| 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 | 100 | 2013 |
| Meta-learning update rules for unsupervised representation learning L Metz, N Maheswaranathan, B Cheung, J Sohl-Dickstein arXiv preprint arXiv:1804.00222, 2018 | 40 | 2018 |
| Superposition of many models into one B Cheung, A Terekhov, Y Chen, P Agrawal, B Olshausen arXiv preprint arXiv:1902.05522, 2019 | 32 | 2019 |
| Convolutional neural networks applied to human face classification B Cheung 2012 11th International Conference on Machine Learning and Applications 2 …, 2012 | 32 | 2012 |
| 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 | 29 | 2014 |
| Learning unsupervised learning rules L Metz, N Maheswaranathan, B Cheung, J Sohl-Dickstein arXiv preprint arXiv:1804.00222, 8, 2018 | 26 | 2018 |
| Emergence of foveal image sampling from learning to attend in visual scenes B Cheung, E Weiss, B Olshausen arXiv preprint arXiv:1611.09430, 2016 | 23 | 2016 |
| 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, ... | 20 | 2012 |
| 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 | 17 | 2009 |
| Hybrid evolution of convolutional networks B Cheung, C Sable 2011 10th International Conference on Machine Learning and Applications and …, 2011 | 14 | 2011 |
| 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 | 12 | 2018 |
| Convolutional vs. recurrent neural networks for audio source separation S Mobin, B Cheung, B Olshausen | 6 | 2018 |
| A neural architecture for representing and reasoning about spatial relationships E Weiss, B Cheung, B Olshausen | 5 | 2016 |
| Fast simultaneous training of generalized linear models (FaSTGLZ) BR Conroy, JM Walz, B Cheung, P Sajda arXiv preprint arXiv:1307.8430, 2013 | 4 | 2013 |
| 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 | 2 | 2020 |
| The motion crisis in functional connectomics: Damage assessment and control for resting-state fMRI C Yan, B Cheung, S Colcombe, RC Craddock, C Kelly, A Di Martino, Q Li, ... F1000Research 3, 2012 | 2 | 2012 |
