Bayesian Learning
A Bayesian network, Bayes network, belief network, Bayes(ian) model or probabilistic directed acyclic graphical model is a probabilistic graphical model (a type of statistical model) that represents a set of variables and their conditional dependencies via a directed acyclic graph (DAG). (Wikipedia)
Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep Learning under Distribution Shift
Neural Information Processing Systems
We compare the algorithms on a wide range of large, convolutional and transformer-based neural network architectures.
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Variational Gaussian Processes For Linear Inverse Problems
Neural Information Processing Systems
By now Bayesian methods are routinely used in practice for solving inverse problems.
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Residual Flows for Invertible Generative Modeling
Tian Qi Chen, Jens Behrmann, David K. Duvenaud, Joern-Henrik Jacobsen
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Neural Information Processing Systems http://nips.cc/
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Bayesian Structure Learning by Recursive Bootstrap
Raanan Y. Rohekar, Yaniv Gurwicz, Shami Nisimov, Guy Koren, Gal Novik
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Neural Information Processing Systems http://nips.cc/
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Nonparametric Bayesian Lomax delegate racing for survival analysis with competing risks
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Neural Information Processing Systems http://nips.cc/
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