Peter J. Sadowski

33 papers A* 1A 1C 1Journal 20Unranked 9

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