BNNs

Approximate blocked Gibbs sampling for Bayesian neural networks
In this work, minibatch MCMC sampling for feedforward neural networks is made more feasible. To this end, it is proposed to sample …
Theodore Papamarkou
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Challenges in Markov chain Monte Carlo for Bayesian neural networks
Markov chain Monte Carlo (MCMC) methods have not been broadly adopted in Bayesian neural networks (BNNs). This paper initially reviews …
Theodore Papamarkou, Jacob Hinkle, M. Todd Young, David Womble
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Wide neural networks with bottlenecks are deep Gaussian processes
There has recently been much work on the ‘wide limit’ of neural networks, where Bayesian neural networks (BNNs) are shown …
Devanshu Agrawal, Theodore Papamarkou, Jacob Hinkle
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