5.7k citations · 15.5k across the 75 of their papers we have counts for
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Rapid Prediction of Electron-Ionization Mass Spectrometry using Neural Networks
Jennifer N. Wei, David Belanger, Ryan P. Adams +1
When confronted with a substance of unknown identity, researchers often perform mass spectrometry on the sample and compare the observed spectrum to a library of previously-collect…
Motivating the Rules of the Game for Adversarial Example Research
Justin Gilmer, Ryan P. Adams, Ian Goodfellow +2
Advances in machine learning have led to broad deployment of systems with impressive performance on important problems. Nonetheless, these systems can be induced to make errors on…
Non-Vacuous Generalization Bounds at the ImageNet Scale: A PAC-Bayesian Compression Approach
Wenda Zhou, Victor Veitch, Morgane Austern +2
Modern neural networks are highly overparameterized, with capacity to substantially overfit to training data. Nevertheless, these networks often generalize well in practice. It has…
Approximate Inference for Constructing Astronomical Catalogs from Images
Jeffrey Regier, Andrew C. Miller, David Schlegel +3
We present a new, fully generative model for constructing astronomical catalogs from optical telescope image sets. Each pixel intensity is treated as a random variable with paramet…
Estimating the Spectral Density of Large Implicit Matrices
Ryan P. Adams, Jeffrey Pennington, Matthew J. Johnson +4
Many important problems are characterized by the eigenvalues of a large matrix. For example, the difficulty of many optimization problems, such as those arising from the fitting of…