https://github.com/francois-rozet/papers-101

Implementation of papers in 101 lines of code.
https://github.com/francois-rozet/papers-101

101 deep-learning generative machine-learning papers research

Last synced: 11 months ago
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Implementation of papers in 101 lines of code.

• Host: GitHub
• URL: https://github.com/francois-rozet/papers-101
• Owner: francois-rozet
• License: mit
• Created: 2023-10-29T10:41:27.000Z (over 2 years ago)
• Default Branch: master
• Last Pushed: 2023-11-12T14:22:42.000Z (over 2 years ago)
• Last Synced: 2025-06-30T13:53:35.646Z (11 months ago)
• Topics: 101, deep-learning, generative, machine-learning, papers, research
• Language: Python
• Homepage:
• Size: 5.86 KB
• Stars: 18
• Watchers: 3
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Papers in 101 lines of code

Implementation of machine learning related papers and algorithms in (more or less) 101 lines of code.

> Inspired by the great [Papers-in-100-Lines-of-Code](https://github.com/MaximeVandegar/Papers-in-100-Lines-of-Code) by [Maxime Vandegar](https://github.com/MaximeVandegar).

## Implemented papers

##### Flow Matching [[code](flow_matching)]

> Flow Matching for Generative Modeling (Lipman et al., 2023) 

> https://openreview.net/forum?id=PqvMRDCJT9t

##### Free-form Flows [[code](free_form_flows)]

> Free-form Flows: Make Any Architecture a Normalizing Flow (Draxler et al., 2023) 

> https://arxiv.org/abs/2310.16624

> Maximum Likelihood Training of Autoencoders (Sorrensonet al., 2023) 

> https://arxiv.org/abs/2306.01843