thu-ml / fpovi
Code for "Function Space Particle Optimization for Bayesian Neural Networks"
☆16Updated 2 years ago
Related projects ⓘ
Alternatives and complementary repositories for fpovi
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated last year
- Stochastic Gradient Langevin Dynamics for Bayesian learning☆30Updated 2 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆80Updated 4 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 4 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆27Updated 3 years ago
- Featurized Density Ratio Estimation☆20Updated 3 years ago
- Codes for "Understanding and Accelerating Particle-Based Variational Inference" (ICML-19)☆22Updated 5 years ago
- Distributional and Outlier Robust Optimization (ICML 2021)☆27Updated 3 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
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 3 years ago
- ☆31Updated 4 years ago
- A pytorch implementation of Amortized Stein Variational Gradient Descent/ Stein GAN☆18Updated 5 years ago
- Code for "A Spectral Approach to Gradient Estimation for Implicit Distributions" (ICML'18)☆32Updated last year
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"☆25Updated 3 years ago
- PyTorch implementation of Stein Variational Gradient Descent☆41Updated last year
- ☆13Updated 5 years ago
- ☆19Updated 4 years ago
- Low-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)☆28Updated 5 years ago
- Variational Auto-Regressive Gaussian Processes for Continual Learning☆20Updated 3 years ago
- Code to minimize the Variational Contrastive Divergence (VCD)☆28Updated 5 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆38Updated 5 years ago
- A tensorflow implementation of the NIPS 2018 paper "Variational Inference with Tail-adaptive f-Divergence"☆20Updated 5 years ago
- Implementation of the Functional Neural Process models☆43Updated 4 years ago
- Code for Accelerated Linearized Laplace Approximation for Bayesian Deep Learning (ELLA, NeurIPS 22')☆16Updated 2 years ago
- Code for A General Recipe for Likelihood-free Bayesian Optimization, ICML 2022☆44Updated 2 years ago
- Tensorflow code for "Hierarchical Decompositional Mixtures of Variational Autoencoders" (ICML'19)☆12Updated 4 years ago
- ☆53Updated 3 months ago
- Code for "Training Deep Energy-Based Models with f-Divergence Minimization" ICML 2020☆35Updated last year