https://github.com/aksub99/ml-for-science
List of papers applying Machine Learning to scientific problems that were discussed in our weekly discussion sessions. Our primary focus is on materials science, molecular optimization and drug discovery.
https://github.com/aksub99/ml-for-science
Last synced: 3 days ago
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List of papers applying Machine Learning to scientific problems that were discussed in our weekly discussion sessions. Our primary focus is on materials science, molecular optimization and drug discovery.
- Host: GitHub
- URL: https://github.com/aksub99/ml-for-science
- Owner: aksub99
- Created: 2020-12-15T05:13:24.000Z (almost 5 years ago)
- Default Branch: main
- Last Pushed: 2021-01-09T18:19:28.000Z (over 4 years ago)
- Last Synced: 2025-02-12T20:17:16.959Z (8 months ago)
- Size: 7.81 KB
- Stars: 3
- Watchers: 3
- Forks: 1
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Weekly discussions on ML for scientific applications
List of papers applying Machine Learning to scientific problems that were discussed in our weekly discussion sessions. Our primary focus is on materials science, molecular optimization and drug discovery.
## 2020
| Date | Topic | Presenters
|:----------------:|:----------------------------------------:|:----------:|
| 14th December, 2020| Molecular De Novo Design through Deep Reinforcement Learning | Akshay
| 21st December, 2020| Grammar Variational Autoencoder | Vignesh
| 29th December, 2020| Inverse Design of Solid-State Materials via a Continuous Representation | Rochan
## 2021
| Date | Topic | Presenters
|:----------------:|:----------------------------------------:|:----------:|
| 6th January, 2021| Barking up the right tree: an approach to search over molecule synthesis DAGs | Akshay