ivannz / mlss2019-bayesian-deep-learningLinks
MLSS2019 Tutorial on Bayesian Deep Learning
☆91Updated 5 years ago
Alternatives and similar repositories for mlss2019-bayesian-deep-learning
Users that are interested in mlss2019-bayesian-deep-learning are comparing it to the libraries listed below
Sorting:
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- The collection of recent papers about variational inference☆85Updated 5 years ago
- The collection of papers about combining deep learning and Bayesian nonparametrics☆120Updated 5 years ago
- a repo sharing Bayesian Neural Network recent papers☆216Updated 5 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆82Updated 11 months ago
- Learning error bars for neural network predictions☆70Updated 5 years ago
- ☆238Updated 5 years ago
- Papers for Bayesian-NN☆323Updated 5 years ago
- Contains code for the NeurIPS 2019 paper "Practical Deep Learning with Bayesian Principles"☆245Updated 5 years ago
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆76Updated last year
- Master Thesis on Bayesian Convolutional Neural Network using Variational Inference☆264Updated 5 years ago
- PyTorch implementation of "Weight Uncertainty in Neural Networks"☆176Updated 3 years ago
- ☆241Updated 2 years ago
- Code for the paper Gaussian process behaviour in wide deep networks☆46Updated 6 years ago
- Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning, ICLR 2020☆235Updated 2 years ago
- Code for Deep Bayesian Active Learning (ICML 2017)☆112Updated 7 years ago
- Implementing Bayes by Backprop☆184Updated 6 years ago
- Code for "A Meta Transfer Objective For Learning To Disentangle Causal Mechanisms"☆127Updated 6 years ago
- Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.☆131Updated 4 years ago
- Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, …☆113Updated 6 years ago
- Implementation and evaluation of different approaches to get uncertainty in neural networks☆140Updated 7 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆89Updated 4 years ago
- This repository is the code for Predictive Uncertainty Estimation using Deep Ensemble☆154Updated 2 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆84Updated 4 years ago
- Original PyTorch implementation of Uncertainty-guided Continual Learning with Bayesian Neural Networks, ICLR 2020☆74Updated 3 years ago
- Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning☆92Updated 4 years ago
- Testing Nerual Tangent Kernel (NTK) on small UCI datasets☆81Updated 5 years ago
- Understanding normalizing flows☆132Updated 5 years ago
- General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.☆38Updated 2 years ago
- ☆61Updated 2 years ago