👀 Overview
Summary | |
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GitHub link | |
Status | NOT STARTED IN PROGRESS COMPLETED WON'T PROGRESS |
\uD83D\uDEA9Â Milestones and metrics
Stage | Milestone/Benchmark | Contributors | Deadline | Status |
|---|---|---|---|---|
Curate training dataset | Work out best level of theory for the training dataset | November 10, 2024 | IN PROGRESS | |
Compute training dataset | December 31, 2024 | NOT STARTED | ||
Curate testing dataset | Compile QM dataset | November 30, 2024 | NOT STARTED | |
Compute QM dataset | January 31, 2025 | NOT STARTED | ||
Compile simulation test set (Free Solv, maybe non-hydration solvation free energy sets that are harder to reproduce) | April 15, 2025 | NOT STARTED | ||
Determine best NN architecture | Implement attention-based GNN | December 31, 2024 | NOT STARTED | |
Implement bond features in GraphSAGE (?) | December 31, 2024 | NOT STARTED | ||
Determine best architecture | January 31, 2025 | NOT STARTED | ||
First pass at NN training | Train using just ESPs, dipoles, quadrupoles | Feb 28, 2025 | NOT STARTED | |
Regularize to RESP charges or MBIS charges if buried atoms are a problem | NOT STARTED | |||
Train directly to charge model if still having issues | NOT STARTED | |||
Benchmark 1: QM | Neural network charge model with low testing error on QM data (ESPs, dipoles) | March 15, 2025 |
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Re-train VDW terms | March 30, 2025 | NOT STARTED | ||
Re-train valence terms | April 15, 2025 | NOT STARTED | ||
Benchmark 2: Simulation | Neural network charge model with equivalent or better performance to NAGL in simulations | April 30, 2025 |