| A deep learning approach to structured signal recovery A Mousavi, AB Patel, RG Baraniuk 2015 53rd annual allerton conference on communication, control, and …, 2015 | 487 | 2015 |
| Firefly-inspired sensor network synchronicity with realistic radio effects G Werner-Allen, G Tewari, A Patel, M Welsh, R Nagpal Proceedings of the 3rd international conference on Embedded networked sensor …, 2005 | 487 | 2005 |
| The emergence of geometric order in proliferating metazoan epithelia MC Gibson, AB Patel, R Nagpal, N Perrimon Nature 442 (7106), 1038-1041, 2006 | 483 | 2006 |
| DESYNC: Self-organizing desynchronization and TDMA on wireless sensor networks J Degesys, I Rose, A Patel, R Nagpal Proceedings of the 6th international conference on Information processing in …, 2007 | 322 | 2007 |
| Training neural networks without gradients: A scalable admm approach G Taylor, R Burmeister, Z Xu, B Singh, A Patel, T Goldstein International conference on machine learning, 2722-2731, 2016 | 293 | 2016 |
| Relgan: Relational generative adversarial networks for text generation W Nie, N Narodytska, A Patel International conference on learning representations, 2018 | 201 | 2018 |
| A theoretical explanation for perplexing behaviors of backpropagation-based visualizations W Nie, Y Zhang, A Patel International conference on machine learning, 3809-3818, 2018 | 154 | 2018 |
| Comparing machine learning algorithms for predicting ICU admission and mortality in COVID-19 S Subudhi, A Verma, AB Patel, CC Hardin, MJ Khandekar, H Lee, ... NPJ digital medicine 4 (1), 87, 2021 | 107 | 2021 |
| A Probabilistic Theory of Deep Learning AB Patel, T Nguyen, RG Baraniuk http://xxx.tau.ac.il/abs/1504.00641, 2015 | 96 | 2015 |
| Desynchronization: The theory of self-organizing algorithms for round-robin scheduling A Patel, J Degesys, R Nagpal First International Conference on Self-Adaptive and Self-Organizing Systems …, 2007 | 90 | 2007 |
| A probabilistic framework for deep learning AB Patel, MT Nguyen, R Baraniuk Advances in neural information processing systems 29, 2016 | 86 | 2016 |
| Automated compilation of probabilistic task description into executable neural network specification AB Patel, RG Baraniuk US Patent 10,846,589, 2020 | 83 | 2020 |
| Modeling and inferring cleavage patterns in proliferating epithelia AB Patel, WT Gibson, MC Gibson, R Nagpal PLoS computational biology 5 (6), e1000412, 2009 | 68 | 2009 |
| Semi-supervised stylegan for disentanglement learning W Nie, T Karras, A Garg, S Debnath, A Patney, A Patel, A Anandkumar International Conference on Machine Learning, 7360-7369, 2020 | 66 | 2020 |
| Epithelial topology R Nagpal, A Patel, MC Gibson BioEssays 30 (3), 260-266, 2008 | 48 | 2008 |
| Towards a better understanding and regularization of GAN training dynamics W Nie, AB Patel Uncertainty in Artificial Intelligence, 281-291, 2020 | 45 | 2020 |
| Deep learning-enhanced variational Monte Carlo method for quantum many-body physics L Yang, Z Leng, G Yu, A Patel, WJ Hu, H Pu Physical Review Research 2 (1), 012039, 2020 | 45 | 2020 |
| Bongard-logo: A new benchmark for human-level concept learning and reasoning W Nie, Z Yu, L Mao, AB Patel, Y Zhu, A Anandkumar Advances in Neural Information Processing Systems 33, 16468-16480, 2020 | 43 | 2020 |
| Domain-driven models yield better predictions at lower cost than reservoir computers in Lorenz systems R Pyle, N Jovanovic, D Subramanian, KV Palem, AB Patel Philosophical Transactions of the Royal Society A 379 (2194), 20200246, 2021 | 20 | 2021 |
| Adversarial attacks on machine learning systems for high-frequency trading M Goldblum, A Schwarzschild, A Patel, T Goldstein Proceedings of the Second ACM International Conference on AI in Finance, 1-9, 2021 | 18 | 2021 |
Radhika NagpalHarvard UniversityVerified email at eecs.harvard.edu
