ermongroup / f-EBM
Code for "Training Deep Energy-Based Models with f-Divergence Minimization" ICML 2020
☆36Updated last year
Alternatives and similar repositories for f-EBM:
Users that are interested in f-EBM are comparing it to the libraries listed below
- ☆53Updated 6 months ago
- [ICML'21] Improved Contrastive Divergence Training of Energy Based Models☆62Updated 2 years ago
- Code for "A Spectral Approach to Gradient Estimation for Implicit Distributions" (ICML'18)☆32Updated last year
- The official code for Efficient Learning of Generative Models via Finite-Difference Score Matching☆11Updated 2 years ago
- Estimating Gradients for Discrete Random Variables by Sampling without Replacement☆40Updated 5 years ago
- Monotone operator equilibrium networks☆51Updated 4 years ago
- ☆12Updated 4 years ago
- Official Release of "Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling"☆49Updated 4 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- Code for the Thermodynamic Variational Objective☆26Updated 2 years ago
- ☆31Updated 4 years ago
- Low-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)☆28Updated 5 years ago
- A tensorflow implementation of the NIPS 2018 paper "Variational Inference with Tail-adaptive f-Divergence"☆20Updated 6 years ago
- A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…☆53Updated 4 months ago
- Code accompanying VarGrad: A Low-Variance Gradient Estimator for Variational Inference☆12Updated 4 years ago
- Low-variance and unbiased gradient for backpropagation through categorical random variables, with application in variational auto-encoder…☆17Updated 4 years ago
- TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".☆60Updated 6 years ago
- Code release for the ICLR paper☆20Updated 6 years ago
- Implementation of the Functional Neural Process models☆43Updated 4 years ago
- Implementation of iterative inference in deep latent variable models☆43Updated 5 years ago
- ☆89Updated 3 years ago
- BIVA: A Very Deep Hierarchy of Latent Variables forGenerative Modeling☆29Updated 5 years ago
- Experiments for the Neural Autoregressive Flows paper☆123Updated 3 years ago
- ☆49Updated 4 years ago
- Exemplar VAE: Linking Generative Models, Nearest Neighbor Retrieval, and Data Augmentation☆69Updated 4 years ago
- A PyTorch Implementation of the Importance Weighted Autoencoders☆40Updated 6 years ago
- ☆37Updated 5 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆63Updated 4 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 3 years ago
- Limitations of the Empirical Fisher Approximation☆47Updated 4 years ago