| Searching for exotic particles in high-energy physics with deep learning P Baldi, P Sadowski, D Whiteson Nature Communications 5, 2014 | 1240 | 2014 |
| Theano: A Python framework for fast computation of mathematical expressions R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, N Ballas, ... arXiv e-prints, arXiv: 1605.02688, 2016 | 1008* | 2016 |
| Understanding dropout P Baldi, P Sadowski Advances in neural information processing systems, 2814-2822, 2013 | 628 | 2013 |
| Learning activation functions to improve deep neural networks F Agostinelli, M Hoffman, P Sadowski, P Baldi arXiv preprint arXiv:1412.6830, 2014 | 548 | 2014 |
| The dropout learning algorithm P Baldi, P Sadowski Artificial intelligence 210, 78-122, 2014 | 308 | 2014 |
| Parameterized neural networks for high-energy physics P Baldi, K Cranmer, T Faucett, P Sadowski, D Whiteson The European Physical Journal C 76, 1-7, 2016 | 282* | 2016 |
| Jet substructure classification in high-energy physics with deep neural networks P Baldi, K Bauer, C Eng, P Sadowski, D Whiteson Physical Review D 93 (9), 094034, 2016 | 248 | 2016 |
| Deep autoencoder neural networks for gene ontology annotation predictions D Chicco, P Sadowski, P Baldi Proceedings of the 5th ACM conference on bioinformatics, computational …, 2014 | 227 | 2014 |
| Decorrelated jet substructure tagging using adversarial neural networks C Shimmin, P Sadowski, P Baldi, E Weik, D Whiteson, E Goul, A Søgaard Physical Review D 96 (7), 074034, 2017 | 138 | 2017 |
| Enhanced Higgs Boson to Search with Deep Learning P Baldi, P Sadowski, D Whiteson Physical review letters 114 (11), 111801, 2015 | 124 | 2015 |
| Sherpa: Robust hyperparameter optimization for machine learning L Hertel, J Collado, P Sadowski, J Ott, P Baldi SoftwareX 12, 100591, 2020 | 109* | 2020 |
| A theory of local learning, the learning channel, and the optimality of backpropagation P Baldi, P Sadowski Neural Networks 83, 51-74, 2016 | 79* | 2016 |
| Learning in the machine: Random backpropagation and the deep learning channel P Baldi, P Sadowski, Z Lu Artificial intelligence 260, 1-35, 2018 | 72 | 2018 |
| Synergies between quantum mechanics and machine learning in reaction prediction P Sadowski, D Fooshee, N Subrahmanya, P Baldi Journal of chemical information and modeling 56 (11), 2125-2128, 2016 | 66 | 2016 |
| Notes on backpropagation P Sadowski Department of Computer ScienceUniversity of California Irvine, 2016 | 44 | 2016 |
| Deep learning, dark knowledge, and dark matter P Sadowski, J Collado, D Whiteson, P Baldi NIPS 2014 Workshop on High-energy Physics and Machine Learning, 81-87, 2015 | 42 | 2015 |
| Panda: Extreme scale parallel k-nearest neighbor on distributed architectures MMA Patwary, NR Satish, N Sundaram, J Liu, P Sadowski, E Racah, ... 2016 IEEE international parallel and distributed processing symposium (IPDPS …, 2016 | 38 | 2016 |
| Revealing fundamental physics from the daya bay neutrino experiment using deep neural networks E Racah, S Ko, P Sadowski, W Bhimji, C Tull, SY Oh, P Baldi 2016 15th IEEE International Conference on Machine Learning and Applications …, 2016 | 36 | 2016 |
| Learning in the machine: the symmetries of the deep learning channel P Baldi, P Sadowski, Z Lu Neural Networks 95, 110-133, 2017 | 26 | 2017 |
| Theano: A Python framework for fast computation of mathematical expressions. arXiv e-prints, abs/1605.02688 R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, N Ballas, ... URL http://arxiv. org/abs/1605.02688, 2016 | 26 | 2016 |
Pierre BaldiProfessor, University of California, IrvineVerified email at ics.uci.edu
