Incorporating Interpretable Output Constraints in Bayesian Neural Networks

Hybrid Monte Carlo

Simon Duane, Anthony D Kennedy, Brian J Pendleton, and Duncan Roweth · 1987

Earlier work this paper cites.

Multilayer Feedforward Networks are Universal Approximators

Kurt Hornik, Maxwell Stinchcombe, and Halbert White · 1989

Earlier work this paper cites.

Keeping the Neural Networks Simple by Minimizing the Description Length of the Weights

Geoffrey E Hinton and Drew Van Camp · 1993

Earlier work this paper cites.

Probable Networks and Plausible Predictions — a Review of Practical Bayesian Methods for Supervised Neural Networks

David J C MacKay · 1995

Earlier work this paper cites.

Bayesian Learning for Neural Networks

Radford M Neal · 1995

Earlier work this paper cites.

Stochastic Differential Equations

Bernt Øksendal · 2003

Earlier work this paper cites.

Pattern Recognition and Machine Learning

Christopher M Bishop · 2006

Earlier work this paper cites.

Adaptive Subgradient Methods for Online Learning and Stochastic Optimization

John Duchi, Elad Hazan, and Yoram Singer · 2011

Earlier work this paper cites.

Practical Variational Inference for Neural Networks

Alex Graves · 2011

Earlier work this paper cites.

Give Me Some Credit

Kaggle · 2011

Earlier work this paper cites.

MCMC Using Hamiltonian Dynamics

Radford M Neal · 2011

Cited alongside, same era.

Auto-Encoding Variational Bayes

Diederik P Kingma and Max Welling · 2014

Cited alongside, same era.

Weight Uncertainty in Neural Networks

Charles Blundell, Julien Cornebise, Koray Kavukcuoglu, and Daan Wierstra · 2015

Cited alongside, same era.

Machine Bias: Risk Assessments in Criminal Sentencing

Julia Angwin, Jeff Larson, Surya Mattu, and Lauren Kirchner · 2016

Cited alongside, same era.

MIMIC-III, A Freely Accessible Critical Care Database

Alistair EW Johnson, Tom J Pollard, Lu Shen, H Lehman Li-wei, Mengling Feng, Mohammad Ghassemi, Benjamin Moody, Peter Szolovits, Leo Anthony Celi, and Roger G Mark · 2016

Cited alongside, same era.

How We Analyzed the COMPAS Recidivism Algorithm

Jeff Larson, Surya Mattu, Lauren Kirchner, and Julia Angwin · 2016

Cited alongside, same era.

Residual Unfairness in Fair Machine Mearning from Prejudiced Data

Nathan Kallus and Angela Zhou · 2018

Later among the works it cites.

Constraining the Dynamics of Deep Probabilistic Models

Marco Lorenzi and Maurizio Filippone · 2018

Later among the works it cites.

Sorting Out Lipschitz Function Approximation

Cem Anil, James Lucas, and Roger Grosse · 2019

Later among the works it cites.

The Functional Neural Process

Christos Louizos, Xiahan Shi, Klamer Schutte, and Max Welling · 2019

Later among the works it cites.

Functional Variational Bayesian Neural Networks

Shengyang Sun, Guodong Zhang, Jiaxin Shi, and Roger Grosse · 2019

Later among the works it cites.

Actionable Recourse in Linear Classification

Berk Ustun, Alexander Spangher, and Yang Liu · 2019

Later among the works it cites.