makora9143 / deterministic-variational-inference-pytorchLinks
☆13Updated 6 years ago
Alternatives and similar repositories for deterministic-variational-inference-pytorch
Users that are interested in deterministic-variational-inference-pytorch are comparing it to the libraries listed below
Sorting:
- Implementation of the Functional Neural Process models☆43Updated 5 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 years ago
- An implementation of a differentiable point process and a differentiable spiking neural network.☆20Updated 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, …☆112Updated 6 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆65Updated 5 years ago
- This repo provides code used in the paper "Predicting with High Correlation Features" (https://arxiv.org/abs/1910.00164):☆54Updated 2 months ago
- A neural network architecture for prediction on sets☆22Updated 3 years ago
- Code for "On the Expressiveness of Approximate Inference in Bayesian Neural Networks"☆13Updated 3 years ago
- Pytorch implementation of Variational Dropout Sparsifies Deep Neural Networks☆83Updated 3 years ago
- Implementation of the paper "Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory", Ron Amit and Ron Meir, ICML 2018☆22Updated 5 years ago
- ☆25Updated 2 years ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- The code for Meta Learning for SGMCMC☆25Updated 6 years ago
- Unsupervised Disentanglement Representation Learning in Chainer☆20Updated 2 years ago
- Code for Self-Tuning Networks (ICLR 2019) https://arxiv.org/abs/1903.03088☆53Updated 6 years ago
- Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"☆44Updated 4 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- Code to accompany the paper Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning☆33Updated 5 years ago
- Python codes for influential instance estimation☆56Updated 2 years ago
- Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning☆92Updated 4 years ago
- Learning error bars for neural network predictions☆71Updated 5 years ago
- PyTorch re-implementation of parts of "Deep Sets" (NIPS 2017)☆71Updated 7 years ago
- SSL using PyTorch☆49Updated 5 years ago
- Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch☆49Updated 7 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆82Updated last year
- Computing various norms/measures on over-parametrized neural networks☆49Updated 6 years ago
- TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".☆60Updated 6 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- #UAI2020 Codes for PAC-Bayesian Contrastive Unsupervised Representation Learning☆12Updated 3 years ago
- "Detecting Extrapolation with Local Ensembles" by David Madras, James Atwood, and Alex D'Amour☆13Updated 4 years ago