ermongroup / dre-infinityLinks
Density Ratio Estimation via Infinitesimal Classification (AISTATS 2022 Oral)
☆20Updated 3 years ago
Alternatives and similar repositories for dre-infinity
Users that are interested in dre-infinity are comparing it to the libraries listed below
Sorting:
- ☆23Updated 3 years ago
- Normalizing Flows with a resampled base distribution☆47Updated 2 years ago
- Codes for ICLR 21 paper: Neural Approximate Sufficient Statistics for Implicit Models☆19Updated 2 years ago
- Stochastic Normalizing Flows☆76Updated 3 years ago
- Discrete Normalizing Flows implemented in PyTorch☆113Updated 3 years ago
- Featurized Density Ratio Estimation☆20Updated 3 years ago
- Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021☆24Updated 2 years ago
- Noise Contrastive Estimation (NCE) in PyTorch☆32Updated 3 months ago
- Sampling with gradient-based Markov Chain Monte Carlo approaches☆101Updated last year
- The official code for Efficient Learning of Generative Models via Finite-Difference Score Matching☆12Updated 2 years ago
- Repo for our paper "Repulsive deep ensembles are Bayesian"☆19Updated 3 years ago
- Code for Knowledge-Adaptation Priors based on the NeurIPS 2021 paper by Khan and Swaroop.☆16Updated 3 years ago
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆19Updated 3 years ago
- PyTorch implementation of Algorithm 1 of "On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Models"☆38Updated 10 months ago
- Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks☆10Updated 2 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- NeurIPS'23: Energy Discrepancies: A Score-Independent Loss for Energy-Based Models☆16Updated 7 months ago
- ☆15Updated 2 years ago
- Lightweight MCMC sampling for PyTorch Models aka My Corona Project☆48Updated last week
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- Official implementation of Transformer Neural Processes☆76Updated 2 years ago
- Official release of code for "Oops I Took A Gradient: Scalable Sampling for Discrete Distributions"☆54Updated last year
- [ICML 2024] Official implementation for "Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling".☆34Updated 5 months ago
- A PyTorch re-implementation of "Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives"☆18Updated 5 years ago
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- Code for reproducing results in the sliced score matching paper (UAI 2019)☆147Updated 5 years ago
- Collecting research materials on neural samplers with diffusion/flow models☆48Updated last week
- Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"☆44Updated 4 years ago
- Official repository for "Categorical Normalizing Flows via Continuous Transformations"☆56Updated 4 years ago
- Bayesian Neural Network Surrogates for Bayesian Optimization☆51Updated last year