Uncertainty in Graph Contrastive Learning with Bayesian Neural Networks
Improving Neural Additive Models with Bayesian Principles
Promises and Pitfalls of the Linearized Laplace in Bayesian Optimization
Meta-learning richer priors for VAEs
Neural Variational Gradient Descent
Pathologies in priors and inference for Bayesian transformers
Quantum Bayesian Neural Networks
A Bayesian Approach to Invariant Deep Neural Networks
Annealed Stein Variational Gradient Descent