9 citations · 26 across the 13 of their papers we have counts for
3 papers · 2 filters
BaCOUn: Bayesian Classifers with Out-of-Distribution Uncertainty
Théo Guénais, Dimitris Vamvourellis, Yaniv Yacoby +2
Traditional training of deep classifiers yields overconfident models that are not reliable under dataset shift. We propose a Bayesian framework to obtain reliable uncertainty estim…
Failure Modes of Variational Autoencoders and Their Effects on Downstream Tasks
Yaniv Yacoby, Weiwei Pan, Finale Doshi-Velez
Variational Auto-encoders (VAEs) are deep generative latent variable models that are widely used for a number of downstream tasks. While it has been demonstrated that VAE training…
Uncertainty-Aware (UNA) Bases for Deep Bayesian Regression Using Multi-Headed Auxiliary Networks
Sujay Thakur, Cooper Lorsung, Yaniv Yacoby +2
Neural Linear Models (NLM) are deep Bayesian models that produce predictive uncertainties by learning features from the data and then performing Bayesian linear regression over the…