Sample code for running deterministic variational inference to train Bayesian neural networks
☆103Oct 10, 2018Updated 7 years ago
Alternatives and similar repositories for deterministic-variational-inference
Users that are interested in deterministic-variational-inference are comparing it to the libraries listed below
Sorting:
- The code for Meta Learning for SGMCMC☆25Feb 21, 2019Updated 7 years ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Apr 4, 2019Updated 6 years ago
- Comparison of Variational Autoencoders with Bayesian Neural Networks. Accuracy, Latent space, Reconstruction and White Noise filtering.☆28Feb 16, 2018Updated 8 years ago
- Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"☆477Jul 6, 2023Updated 2 years ago
- UAI paper 'Expressive Priors in Bayesian Neural Networks: Kernel Combinations and Periodic Functions'☆11Jun 26, 2019Updated 6 years ago
- Bayesian Deep Learning Benchmarks☆673Mar 24, 2023Updated 2 years ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Nov 14, 2019Updated 6 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆82Jun 17, 2024Updated last year
- Pytorch optimizers implementing Hilbert Constrained Gradient Descent☆19May 9, 2019Updated 6 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆65Jul 17, 2020Updated 5 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆86Jul 19, 2020Updated 5 years ago
- A community repository for benchmarking Bayesian methods☆112Nov 29, 2021Updated 4 years ago
- a repo sharing Bayesian Neural Network recent papers☆216Aug 9, 2019Updated 6 years ago
- ☆14Aug 20, 2019Updated 6 years ago
- A pytorch version of hamiltonian monte carlo☆15Jun 26, 2019Updated 6 years ago
- Learning Generative Models across Incomparable Spaces (ICML 2019)☆28Mar 11, 2020Updated 6 years ago
- PyTorch implementation of "Weight Uncertainty in Neural Networks"☆176Apr 12, 2022Updated 3 years ago
- ☆53May 4, 2018Updated 7 years ago
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆78Oct 3, 2023Updated 2 years ago
- ☆12Jul 16, 2023Updated 2 years ago
- Code for "Adversarial Distillation of Bayesian Neural Network Posteriors" https://arxiv.org/abs/1806.10317☆16Oct 31, 2018Updated 7 years ago
- Experiments used in "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"☆581Feb 26, 2022Updated 4 years ago
- Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more☆1,960Oct 20, 2023Updated 2 years ago
- Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch☆362Oct 12, 2019Updated 6 years ago
- A tensorflow implementation of VAE training with Renyi divergence☆31Sep 14, 2016Updated 9 years ago
- Reproducing the paper "The continuous Bernoulli: fixing a pervasive error in variational autoencoders" for the Reproducibility Challenge …☆12Jul 25, 2024Updated last year
- Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference, Gal et al. 2015☆36May 21, 2018Updated 7 years ago
- Source code for paper Conservative Uncertainty Estimation By Fitting Prior Networks (ICLR 2020)☆22Nov 28, 2022Updated 3 years ago
- Pytorch version of "Deep Convolutional Networks as shallow Gaussian Processes" by Adrià Garriga-Alonso, Carl Rasmussen and Laurence Aitch…☆32Apr 16, 2020Updated 5 years ago
- Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning☆93Oct 28, 2020Updated 5 years ago
- ☆52Feb 27, 2023Updated 3 years ago
- Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.☆1,568Apr 19, 2024Updated last year
- Scalable Bayes via Barycenter in Wasserstein Space☆10Sep 7, 2017Updated 8 years ago
- Variational Auto-Regressive Gaussian Processes for Continual Learning☆22Jun 15, 2021Updated 4 years ago
- Code for the paper "Marginalized Average Attentional Network for Weakly-Supervised Learning" (ICLR 2019)☆34Mar 27, 2019Updated 6 years ago
- customized GPflow with simple Tensorflow API☆17Aug 7, 2019Updated 6 years ago
- TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".☆60Jan 12, 2019Updated 7 years ago
- PyTorch-SSO: Scalable Second-Order methods in PyTorch☆149Oct 1, 2023Updated 2 years ago
- Original PyTorch implementation of Uncertainty-guided Continual Learning with Bayesian Neural Networks, ICLR 2020☆76Jun 15, 2021Updated 4 years ago