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07/02/2023
Tools for Verifying Neural Models' Training Data
It is important that consumers and regulators can verify the provenance ...
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02/12/2021
Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations
We perform scalable approximate inference in a recently-proposed family ...
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07/09/2020
A Study of Gradient Variance in Deep Learning
The impact of gradient noise on training deep models is widely acknowled...
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03/05/2020
What went wrong and when? Instance-wise Feature Importance for Time-series Models
Multivariate time series models are poised to be used for decision suppo...
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02/13/2020
Cutting out the Middle-Man: Training and Evaluating Energy-Based Models without Sampling
We present a new method for evaluating and training unnormalized density...
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10/02/2018
FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models
A promising class of generative models maps points from a simple distrib...
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12/17/2017
