rosinality / igebm-pytorchLinks
Implicit Generation and Generalization in Energy Based Models in PyTorch
☆66Updated 6 years ago
Alternatives and similar repositories for igebm-pytorch
Users that are interested in igebm-pytorch are comparing it to the libraries listed below
Sorting:
- Code for reproducing Flow ++ experiments☆190Updated 6 years ago
- Official PyTorch BIVA implementation (BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling)☆85Updated 2 years ago
- Official Release of "Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling"☆49Updated 5 years ago
- ☆26Updated 6 years ago
- Implementation of Glow in PyTorch☆80Updated 4 years ago
- PyTorch Implementation of Neural Statistician☆61Updated 3 years ago
- PyTorch code accompanying our paper on Maximum Entropy Generators for Energy-Based Models☆154Updated 6 years ago
- Hybrid Discriminative-Generative Training via Contrastive Learning☆75Updated 2 years ago
- Real NVP PyTorch a Minimal Working Example | Normalizing Flow☆142Updated 5 years ago
- ☆53Updated 4 years ago
- code for "Residual Flows for Invertible Generative Modeling".☆273Updated 2 years ago
- Reference implementation of divergence triangle https://arxiv.org/abs/1812.10907☆16Updated 2 years ago
- ☆79Updated 7 months ago
- Code for "Training Deep Energy-Based Models with f-Divergence Minimization" ICML 2020☆36Updated 2 years ago
- A PyTorch Implementation of the Importance Weighted Autoencoders☆39Updated 7 years ago
- ☆64Updated last year
- Implementation of Real NVP in PyTorch☆236Updated 6 years ago
- Code for reproducing results in the sliced score matching paper (UAI 2019)☆148Updated 5 years ago
- ☆32Updated 5 years ago
- The official code for Efficient Learning of Generative Models via Finite-Difference Score Matching☆12Updated 3 years ago
- ☆32Updated 4 years ago
- ☆91Updated 6 years ago
- ☆149Updated 3 years ago
- Code for paper "Closing the Dequantization Gap: PixelCNN as a Single-Layer Flow"☆19Updated 5 years ago
- Code for "Flow-GAN: Combining Maximum Likelihood and Adversarial Learning in Generative Models", AAAI 2018.☆111Updated 7 years ago
- Discrete Normalizing Flows implemented in PyTorch☆113Updated 4 years ago
- ☆181Updated 6 years ago
- ☆42Updated 6 years ago
- ☆238Updated 6 years ago
- This repository contains the 3D shapes dataset, used in Kim, Hyunjik and Mnih, Andriy. "Disentangling by Factorising." In Proceedings of …☆152Updated last year