This release adds a deep learning edition with 6 new talktorials. An overview is given in the pre-print TeachOpenCADD goes Deep Learning: Open-source Teaching Platform Exploring Molecular DL Applications.
More details below.
What's changed
New talktorials
- T033: Molecular representations by @gerritgr #314
- T034: Recurrent neural networks for molecular property prediction by @azmtag #320
- T035: Graph neural networks for molecular property prediction by @PaulaKramer #287
- T036: E(3)-equivariant graph neural network for molecular property prediction by @joschka-gross #326
- T037: Uncertainty estimation by @mbackenkoehler #286
- T038: Protein ligand interaction prediction by @Old-Shatterhand #290
Fixes
- Updated environment for new notebooks and integrate into CI by @mbackenkoehler
- Additional notebook reviews by @f-sod, @hamzaibrahim21, @verenawolf and @AndreaVolkamer
- Added talktorials on the website @PaulaKramer #384
- T020: Fixed typo by @jaketanderson #383
Notes
- Talktorials T035, T036, and T038 currently require a manual installation of pytorch-geometric
- Some talktorials are ignored in the CI because they may require repeated executions, mainly due to the use of online APIs. #382
New contributors - Thanks!
- @gerritgr
- @azmtag
- @joschka-gross
- @Old-Shatterhand
- @f-sod
- @jaketanderson
- Verena Wolf
Contributors
mbackenkoehler, gerritgr, and 9 other contributors
Assets 2
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