Skip to content
conftrace_

weight posterior

5 papers

Explore in graph

Co-occurring keywords · papers mentioning both

variational inference (4) bayesian neural network (2) stochastic process (2) mean-field approximation (2) kl divergence (2) parameter-free training (1) mislabeled sample (1) discrete weight (1) expectation backpropagation (1) sample informativeness (1)

Papers

Laplace Sample Information: Data Informativeness Through a Bayesian Lens ICLR 2025 Wide Bayesian neural networks have a simple weight posterior: theory and accelerated sampling ICML 2022 Liberty or Depth: Deep Bayesian Neural Nets Do Not Need Complex Weight Posterior Approximations NeurIPS 2020 Stochastic gradient descent performs variational inference, converges to limit cycles for deep networks ICLR 2018 Expectation Backpropagation: Parameter-Free Training of Multilayer Neural Networks with Continuous or Discrete Weights NeurIPS 2014