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CompChem Highlights
@CCHighlights
Important recent papers in computational and theoretical chemistry A free resource for scientists run by scientists
Joined February 2012
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CompChem Highlights
@CCHighlights
over 1 year ago
Lifelong Machine Learning Potentials https://t.co/28XTKGHvbU
#compchem
CompChem Highlights
@CCHighlights
almost 2 years ago
Toy Models of Superposition https://t.co/opkd7ljdie
CompChem Highlights
@CCHighlights
almost 2 years ago
Variational Pair-Density Functional Theory: Dealing with Strong Correlation at the Protein Scale https://t.co/P2HPdm8czG
#compchem
CompChem Highlights
@CCHighlights
almost 2 years ago
Reproducing Reaction Mechanisms with Machine Learning Models Trained on a Large-Scale Mechanistic Dataset https://t.co/wGUx8GDhg0
#compchem
Who to follow
Pavlo Dral
@PavloDral
Professor at Xiamen University, theoretical chemist, #compchem, #ML, #AI, #mlchem Ukrainian
William L. Jorgensen
@JorgensenWL
Chemistry Prof @ Yale; founding Editor JCTC; OPLS, TIPnP, FEP, Drug Design
Mario Barbatti
@MarioBarbatti
Theoretical chemist and physicist Professor Aix Marseille Univ Senior member @InstUnivFr Head of the ICR #TheoChem group https://t.co/xTjlPkUqCQ
CompChem Highlights
@CCHighlights
about 2 years ago
Using GNN property predictors as molecule generators https://t.co/FgdlkKkouI
#compchem
CompChem Highlights
@CCHighlights
about 2 years ago
FragGT: Fragment-based evolutionary molecule generation with gene types https://t.co/spRl9QyIhd
#compchem
CompChem Highlights
@CCHighlights
about 2 years ago
@wangleiphy
Except that SELFIES were invented specifically to always give valid molecules. If you filter out molecules, then the raison d'être for SELFIES (which arguably has a syntax that is more difficult to learn) disappears.
CompChem Highlights
@CCHighlights
about 2 years ago
@gklambauer
If SELFIES is a harder syntax to learn, isn't it all the more important to remove the cases where it goes wrong?
CompChem Highlights
@CCHighlights
about 2 years ago
Invalid SMILES are beneficial rather than detrimental to chemical language models https://t.co/P9XDwuhfVH
#compchem
CompChem Highlights
@CCHighlights
over 2 years ago
An evolutionary algorithm for interpretable molecular representations https://t.co/n2eo6YOdqg
#compchem
CompChem Highlights
@CCHighlights
over 2 years ago
AiZynth Impact on Medicinal Chemistry Practice at AstraZeneca https://t.co/zAN8kjQioG
#compchem
CompChem Highlights
@CCHighlights
over 2 years ago
TS-Tools: Rapid and Automated Localization of Transition States Based on a Textual Reaction SMILES Input https://t.co/FYQg7HaVT2
#compchem
CompChem Highlights
@CCHighlights
over 2 years ago
Accurate transition state generation with an object-aware equivariant elementary reaction diffusion model https://t.co/JvtN1sGkps
#compchem
CompChem Highlights
@CCHighlights
over 2 years ago
Growing strings in a chemical reaction space for searching retrosynthesis pathways https://t.co/sStrc0Bn9S
#compchem
CompChem Highlights
@CCHighlights
over 2 years ago
Few-Shot Learning for Low-Data Drug Discovery https://t.co/OQoTOZLcZx
#compchem
CompChem Highlights
@CCHighlights
almost 3 years ago
Ranking Pareto optimal solutions based on projection free energy https://t.co/ackF6LNcUs
#compchem
CompChem Highlights
@CCHighlights
almost 3 years ago
Accelerated dinuclear palladium catalyst identification through unsupervised machine learning https://t.co/27aPEt81WP
#compchem
CompChem Highlights
@CCHighlights
almost 3 years ago
Real-World Molecular Out-Of-Distribution: Specification and Investigation https://t.co/W3FMOnyih8
#compchem
CompChem Highlights
@CCHighlights
about 3 years ago
Evolutionary Multiobjective Optimization of Multiligand Metal Complexes in Diverse and Vast Chemical Spaces https://t.co/r35wvfz5V3
#compchem
CompChem Highlights
@CCHighlights
about 3 years ago
Seeing is Believing: Brain-Inspired Modular Training for Mechanistic Interpretability https://t.co/Kdpay5W5sE
#compchem
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