trevorcampbell / bayesian-coresets
Automated Scalable Bayesian Inference
☆129Updated 2 years ago
Related projects ⓘ
Alternatives and complementary repositories for bayesian-coresets
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆80Updated 4 months ago
- A community repository for benchmarking Bayesian methods☆109Updated 2 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆55Updated 3 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆63Updated 5 years ago
- ☆158Updated 3 months ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆80Updated 4 years ago
- Code for the paper Gaussian process behaviour in wide deep networks☆48Updated 6 years ago
- OxCSML research group reading groups and meetings at the Department of Statistics, University of Oxford.☆92Updated 2 years ago
- Deep Gaussian Processes with Doubly Stochastic Variational Inference☆147Updated 5 years ago
- Convolutional Neural Tangent Kernel☆107Updated 5 years ago
- python code for kernel methods☆36Updated 5 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 6 years ago
- Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning☆91Updated 4 years ago
- Contains code for the NeurIPS 2019 paper "Practical Deep Learning with Bayesian Principles"☆242Updated 4 years ago
- PyTorch-SSO: Scalable Second-Order methods in PyTorch☆141Updated last year
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 4 years ago
- Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)☆42Updated 3 years ago
- Deep neural network kernel for Gaussian process☆198Updated 4 years ago
- Gaussian Processes for Sequential Data☆18Updated 3 years ago
- Deep convolutional gaussian processes.☆78Updated 5 years ago
- This repository contains the Python code to reproduce all the figures and experiments presented in the paper: Masegosa, Andrés. R., Learn…☆9Updated last year
- This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).☆46Updated 3 years ago
- Calibration library and code for the paper: Verified Uncertainty Calibration. Ananya Kumar, Percy Liang, Tengyu Ma. NeurIPS 2019 (Spotlig…☆142Updated last year
- The collection of recent papers about variational inference☆84Updated 5 years ago
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 3 years ago
- Large-scale, multi-GPU capable, kernel solver☆181Updated 3 months ago
- Random Fourier Features☆49Updated 7 years ago
- Dirichlet MLE python library☆113Updated 7 months ago
- Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, …☆110Updated 5 years ago