yataobian / awesome-ebm
Collecting research materials on energy/entropy based models
Why this job: name: awesome
What it does
A tutorial on energy-based learning. Predicting structured data, 1(0), 2006](http://web.stanford.edu/class/cs379c/archive/2012/suggested_reading_list/documents/LeCunetal06.pdf)
Get started
No single install command. Read the steps in the README (opens in new tab)
- Maintenance
- Inactive
- Last commit 6 months ago
- Stars
- 402
- On GitHub
- Licence
- MIT
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- None yet
- No releases
- Built with
- Shell
- 100% of the code
Is it looked after?
- Contributors
- Not stated
- Last 90 days
- Issues
- 100% closed
- 0 still open
- Pull requests
- 5 merged
- 0 waiting
- Releases
- None
- Never published
- No contributing guide
- No security policy
- No code of conduct
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| Repo | Stars | Last commit | Licence | Downloads for |
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| amirhossein-kz / Awesome-Diffusion-Models-in-Medical-Imaging | 2,116 | 12 months ago | MIT | No downloads |
More: languages, topics and project record
Languages
- Shell 100%
Topics
- energy
- energy-based-model
- energy-based-learning
- machine-learning
- exponential-family
- energy-based-machine-learning
- energy-based-deep-learning
- energy-based-graph-learning
- deep-learning
- score-matching
- contrastive-divergence
- noise-contrastive-estimation
Project record
- JobLists and guides
- StatusListed
- Commits115
- Forks35
- Watching24
- Stars in 28 days+3
- CreatedApr 15, 2021
- First seen by usNov 7, 2026
- CheckedNov 8, 2026