bayinf / awesome-variational-inferenceLinks
A curated list of awesome variational inference
☆26Updated 5 years ago
Alternatives and similar repositories for awesome-variational-inference
Users that are interested in awesome-variational-inference are comparing it to the libraries listed below
Sorting:
- The collection of papers about combining deep learning and Bayesian nonparametrics☆121Updated 5 years ago
- The collection of recent papers about variational inference☆85Updated 5 years ago
- Code for ICE-BeeM paper - NeurIPS 2020☆87Updated 4 years ago
- Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)☆205Updated 3 years ago
- Classifier based mutual information, conditional mutual information estimation; conditional independence testing☆34Updated 6 years ago
- Testing methods for estimating KL-divergence from samples.☆66Updated 6 months ago
- code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"☆100Updated 6 years ago
- Papers for Bayesian-NN☆325Updated 6 years ago
- ☆243Updated 2 years ago
- Regression datasets from the UCI repository with standardized test-train splits.☆47Updated 3 years ago
- Implementation of "DAGs with NO TEARS: Smooth Optimization for Structure Learning", by Zheng et al. (2018)☆49Updated 6 years ago
- This repository is the code for Predictive Uncertainty Estimation using Deep Ensemble☆157Updated 3 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆89Updated 5 years ago
- Variational Inference in Gaussian Mixture Model☆60Updated 4 years ago
- ☆238Updated 5 years ago
- Official Implementation of "Transformers Can Do Bayesian Inference", the PFN paper☆232Updated 10 months ago
- Pytorch implementation of Neural Processes for functions and images☆233Updated 3 years ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆26Updated last year
- Code for the paper "Bayesian Neural Network Priors Revisited"☆58Updated 4 years ago
- Code for "Causal autoregressive flows" - AISTATS, 2021☆45Updated 4 years ago
- PyTorch implementation of "Weight Uncertainty in Neural Networks"☆176Updated 3 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆85Updated 5 years ago
- Code for random Fourier features based on Rahimi and Recht's 2007 paper.☆57Updated 4 years ago
- A community repository for benchmarking Bayesian methods☆110Updated 3 years ago
- Reimplementation of Variational Inference with Normalizing Flows (https://arxiv.org/abs/1505.05770)☆235Updated 7 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated last year
- Amortized Inference for Causal Structure Learning, NeurIPS 2022☆67Updated 7 months ago
- demonstration of the information bottleneck theory for deep learning☆66Updated 7 years ago
- Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances☆48Updated 2 years ago
- ☆40Updated 5 years ago