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Bivariate Causal Discovery using Bayesian Model Selection

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Learning in Deep Factor Graphs with Gaussian Belief Propagation

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Noether' s Razor: Learning Conserved Quantities

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Recommendations for Baselines and Benchmarking Approximate Gaussian Processes

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Transition Constrained Bayesian Optimization via Markov Decision Processes

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Actually Sparse Variational Gaussian Processes

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Learning Layer-wise Equivariances Automatically using Gradients

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Stochastic Marginal Likelihood Gradients using Neural Tangent Kernels

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Bayesian Neural Network Priors Revisited

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Data augmentation in Bayesian neural networks and the cold posterior effect

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