cambridge-mlg / expressiveness-approx-bnns
Code for "On the Expressiveness of Approximate Inference in Bayesian Neural Networks"
☆13Updated 3 years ago
Alternatives and similar repositories for expressiveness-approx-bnns:
Users that are interested in expressiveness-approx-bnns are comparing it to the libraries listed below
- Code for Unbiased Implicit Variational Inference (UIVI)☆14Updated 6 years ago
- Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)☆42Updated 3 years ago
- Benchmark functions for Bayesian optimization☆33Updated last year
- Code to accompany the paper Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning☆33Updated 4 years ago
- ☆49Updated 4 years ago
- ☆37Updated 5 years ago
- ☆53Updated 8 months ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 3 years ago
- Implementation of Normalizing flows on MNIST https://arxiv.org/abs/1505.05770☆14Updated 6 years ago
- ☆16Updated 6 years ago
- Code for Augment & Reduce, a scalable stochastic algorithm for large categorical distributions☆10Updated 6 years ago
- A pytorch implementation of Amortized Stein Variational Gradient Descent/ Stein GAN☆18Updated 6 years ago
- ☆26Updated 5 years ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- Code for "Exponential Family Estimation via Adversarial Dynamics Embedding" (NeurIPS 2019)☆13Updated 5 years ago
- Jupyter Notebook corresponding to 'Going with the Flow: An Introduction to Normalizing Flows'☆25Updated 3 years ago
- Stochastic Gradient Langevin Dynamics for Bayesian learning☆31Updated 3 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- Implementation of the Functional Neural Process models☆43Updated 4 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated 9 months ago
- Code to minimize the Variational Contrastive Divergence (VCD)☆29Updated 5 years ago
- BIVA: A Very Deep Hierarchy of Latent Variables forGenerative Modeling☆29Updated 5 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆82Updated 4 years ago
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 4 years ago
- Limitations of the Empirical Fisher Approximation☆47Updated 3 weeks ago
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- Computing the eigenvalues of Neural Tangent Kernel and Conjugate Kernel (aka NNGP kernel) over the boolean cube☆47Updated 5 years ago
- PyTorch implementation of Continuously Indexed Flows paper, with many baseline normalising flows☆31Updated 3 years ago
- Sparse Orthogonal Variational Inference for Gaussian Processes (SOLVE-GP)☆22Updated 3 years ago