https://github.com/jxzhangjhu/awesome-energy-based-model

Energy-based model
https://github.com/jxzhangjhu/awesome-energy-based-model

List: awesome-energy-based-model

Last synced: about 1 month ago
JSON representation

Energy-based model

• Host: GitHub
• URL: https://github.com/jxzhangjhu/awesome-energy-based-model
• Owner: jxzhangjhu
• License: mit
• Created: 2021-02-25T03:26:34.000Z (over 3 years ago)
• Default Branch: main
• Last Pushed: 2021-03-02T18:34:03.000Z (over 3 years ago)
• Last Synced: 2024-04-10T03:39:23.171Z (5 months ago)
• Size: 8.79 KB
• Stars: 4
• Watchers: 4
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: license

Awesome Lists containing this project

• ultimate-awesome - awesome-energy-based-model - Energy-based model . (Other Lists / PowerShell Lists)

README

        


## 📝 Publications

1. ICLR 2021 - [Generalized Energy Based Models](https://arxiv.org/abs/2003.05033) by Michael Arbel et. al.

   >[Github Code](https://github.com/MichaelArbel/GeneralizedEBM)

   

2. ICLR 2021 - [No MCMC for me: Amortized sampling for fast and stable training of energy-based models](https://arxiv.org/abs/2010.04230) by Will Grathwohl et al.

   >[Github Code](https://github.com/wgrathwohl/VERA)

3. NeurIPS 2019 - [Implicit Generation and Modeling with Energy-Based Models](https://arxiv.org/abs/1903.08689) by YiLun Du and Igor Mordatch

   >[Github Code](https://github.com/openai/ebm_code_release)

4. ICLR 2020 - [Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One](https://arxiv.org/abs/1912.03263) by Will Grathwohl et al.

   >[Github Code](https://github.com/wgrathwohl/JEM)

5. ICML 2020  - [Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling](https://arxiv.org/abs/2002.05616) by Will Grathwohl et al.

   >[Github Code](https://github.com/wgrathwohl/LSD)

6. CVPR 2020 - [Flow Contrastive Estimation of Energy-Based Models](https://openaccess.thecvf.com/content_CVPR_2020/papers/Gao_Flow_Contrastive_Estimation_of_Energy-Based_Models_CVPR_2020_paper.pdf) by Ruiqi Gao et al.

   >[Github Code: not available]

7. ICLR 2021 - [Learning Energy-Based Models by Diffusion Recovery Likelihood](http://www.stat.ucla.edu/~ruiqigao/drl/paper.pdf) by Ruiqi Gao et al.

   >[Github Code: not available]

8. Arxiv 2021 - [How to Train Your Energy-Based Models](https://arxiv.org/abs/2101.03288) by 

   >[Github Code: not available]

9. ICLR 2021 - [VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models](https://arxiv.org/abs/2010.00654)

   >[Github Code: not available]

10.