Peter J. Sadowski

ORCID

Publication Activity (10 Years)

Years Active: 2010-2021
Publications (10 Years): 24

Top Venues

University of California, Irvine, USA (PHD)

Education History

University of California, Irvine, USA

PHD

Publications

Mohammadamin Tavakoli, Peter J. Sadowski, Pierre Baldi
Tourbillon: a Physically Plausible Neural Architecture. CoRR (2021)
Brandon Quach, Yannik Glaser, Justin Edward Stopa, Alexis Aurelien Mouche, Peter J. Sadowski
Deep Learning for Predicting Significant Wave Height From Synthetic Aperture Radar. IEEE Trans. Geosci. Remote. Sens. 59 (3) (2021)
Michael Ito, Yannik Glaser, Peter J. Sadowski
Evolution-Informed Neural Networks for Microbiome Data Analysis. BIBM (2021)
Brandon Quach, Yannik Glaser, Justin Stopa, Peter J. Sadowski
Deep Sensing of Ocean Wave Heights with Synthetic Aperture Radar. AAAI Spring Symposium: MLPS (2020)
Lars Hertel, Julian Collado, Peter J. Sadowski, Jordan Ott, Pierre Baldi
Sherpa: Robust hyperparameter optimization for machine learning. SoftwareX 12 (2020)
Lars Hertel, Julian Collado, Peter J. Sadowski, Jordan Ott, Pierre Baldi
Sherpa: Robust Hyperparameter Optimization for Machine Learning. CoRR (2020)
Pierre Baldi, Peter J. Sadowski, Zhiqin Lu
Learning in the Machine: Random Backpropagation and the Deep Learning Channel (Extended Abstract). IJCAI (2019)
Pierre Baldi, Peter J. Sadowski, Zhiqin Lu
Learning in the machine: Random backpropagation and the deep learning channel. Artif. Intell. 260 (2018)
Pierre Baldi, Peter J. Sadowski
Learning in the machine: Recirculation is random backpropagation. Neural Networks 108 (2018)
Peter J. Sadowski, Pierre Baldi
Deep Learning in the Natural Sciences: Applications to Physics. Braverman Readings in Machine Learning (2017)
Pierre Baldi, Peter J. Sadowski, Zhiqin Lu
Learning in the Machine: the Symmetries of the Deep Learning Channel. CoRR (2017)
Pierre Baldi, Peter J. Sadowski, Zhiqin Lu
Learning in the machine: The symmetries of the deep learning channel. Neural Networks 95 (2017)
Peter J. Sadowski, Balint Radics, Ananya, Yasunori Yamazaki, Pierre Baldi
Efficient Antihydrogen Detection in Antimatter Physics by Deep Learning. CoRR (2017)
Pierre Baldi, Kyle Cranmer, Taylor Faucett, Peter J. Sadowski, Daniel Whiteson
Parameterized Machine Learning for High-Energy Physics. CoRR (2016)
Md. Mostofa Ali Patwary, Nadathur Rajagopalan Satish, Narayanan Sundaram, Jialin Liu, Peter J. Sadowski, Evan Racah, Surendra Byna, Craig Tull, Wahid Bhimji, Prabhat, Pradeep Dubey
PANDA: Extreme Scale Parallel K-Nearest Neighbor on Distributed Architectures. CoRR (2016)
Pierre Baldi, Peter J. Sadowski
A theory of local learning, the learning channel, and the optimality of backpropagation. Neural Networks 83 (2016)
Peter J. Sadowski, David Fooshee, Niranjan Subrahmanya, Pierre Baldi
Synergies Between Quantum Mechanics and Machine Learning in Reaction Prediction. J. Chem. Inf. Model. 56 (11) (2016)
Md. Mostofa Ali Patwary, Nadathur Rajagopalan Satish, Narayanan Sundaram, Jialin Liu, Peter J. Sadowski, Evan Racah, Surendra Byna, Craig Tull, Wahid Bhimji, Prabhat, Pradeep Dubey
PANDA: Extreme Scale Parallel K-Nearest Neighbor on Distributed Architectures. IPDPS (2016)
Evan Racah, Seyoon Ko, Peter J. Sadowski, Wahid Bhimji, Craig Tull, Sang-Yun Oh, Pierre Baldi, Prabhat
Revealing Fundamental Physics from the Daya Bay Neutrino Experiment Using Deep Neural Networks. ICMLA (2016)
Pierre Baldi, Peter J. Sadowski, Zhiqin Lu
Learning in the Machine: Random Backpropagation and the Learning Channel. CoRR (2016)
Evan Racah, Seyoon Ko, Peter J. Sadowski, Wahid Bhimji, Craig Tull, Sang-Yun Oh, Pierre Baldi, Prabhat
Revealing Fundamental Physics from the Daya Bay Neutrino Experiment using Deep Neural Networks. CoRR (2016)
Michael Biehl, Peter J. Sadowski, Gyan Bhanot, Erhan Bilal, Adel Dayarian, Pablo Meyer, Raquel Norel, Kahn Rhrissorrakrai, Michael D. Zeller, Sahand Hormoz
Inter-species prediction of protein phosphorylation in the sbv IMPROVER species translation challenge. Bioinform. 31 (4) (2015)
Pierre Baldi, Peter J. Sadowski
The Ebb and Flow of Deep Learning: a Theory of Local Learning. CoRR (2015)
Forest Agostinelli, Matthew D. Hoffman, Peter J. Sadowski, Pierre Baldi
Learning Activation Functions to Improve Deep Neural Networks. ICLR (Workshop) (2015)
Peter J. Sadowski, Julian Collado, Daniel Whiteson, Pierre Baldi
Deep Learning, Dark Knowledge, and Dark Matter. HEPML@NIPS (2014)
Pierre Baldi, Peter J. Sadowski, Daniel Whiteson
Enhanced Higgs to $τ^+τ^-$ Searches with Deep Learning. CoRR (2014)
Pierre Baldi, Peter J. Sadowski
The dropout learning algorithm. Artif. Intell. 210 (2014)
Peter J. Sadowski, Daniel Whiteson, Pierre Baldi
Searching for Higgs Boson Decay Modes with Deep Learning. NIPS (2014)
Davide Chicco, Peter J. Sadowski, Pierre Baldi
Deep autoencoder neural networks for gene ontology annotation predictions. BCB (2014)
Pierre Baldi, Peter J. Sadowski
Understanding Dropout. NIPS (2013)
Peter J. Sadowski, Pierre Baldi
Small-Molecule 3D Structure Prediction Using Open Crystallography Data. J. Chem. Inf. Model. 53 (12) (2013)
Peter J. Sadowski, Luca Cazzanti, Maya R. Gupta
Bayesian and pairwise local similarity discriminant analysis. CIP (2010)

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Publication Activity (10 Years)

Top Topics

Top Venues

Peter J. Sadowski