exmol

• Getting Started
  • Install
  • Quickstart
  • Counterfactual Generation
  • Descriptor Attribution
  • Usage
  • Further Examples
  • Chemical Space
  • SVG
  • Disable Progress Bars
  • API and Docs
  • Developing
  • Citation
• Change Log
  • v3.0.3 (2023-06-19)
  • v3.0.2 (2023-02-23)
  • v3.0.1 (2023-02-02)
  • v3.0.0 (2023-01-24)
  • v2.2.1 (2022-12-7)
  • v2.2.0 (2022-11-3)
  • v2.1.1 (2022-6-03)
  • v2.1.0 (2022-6-03)
  • v2.0.1 (2022-5-31)
  • v2.0.0 (2022-5-31)
  • v1.1.0 (2022-5-2)
  • v1.0.2 (2022-5-2)
  • v1.0.1 (2022-4-4)
  • v1.0.0 (2022-1-21)
  • v0.6.0 (2022-1-17)
  • v0.5.2 (2022-1-4)
  • v0.5.1 (2021-11-16)
  • v0.5.0 (2021-10-26)
  • v0.4.1 (2021-09-27)
  • v0.4.0 (2021-09-17)
  • v0.3.2 (2021-09-02)
  • v0.3.1 (2021-08-26)
  • v0.3.0 (2021-08-25)
  • v0.2.0 (2021-08-14)
• API
• Tutorial
  • Counterfacutal explanations
  • Explain using substructures
  • Text
• MMACE Paper: Counterfactual Example
• MMACE Paper: Random Forest for Blood-Brain Barrier
  • Schematic Plots
  • Chemed
• MMACE Paper: Graph Neural Network for HIV Inhibition
  • CF explanation
• MMACE Paper: Recurrent Neural Network for Predicting Solubility
  • CF explanation:
  • Figure showing effect of mutation number and Alphabet
• LIME paper: Recurrent Neural Network for Solubility Prediciton
  • Import packages and set up RNN
  • LIME explanations
  • Robustness to incomplete sampling
  • Effect of mutation number, alphabet and size of chemical space
• LIME paper: Random Forest for Solubility Prediciton
  • Import packages
  • Build and train a Random Forest model
  • Compute descriptor attributions
  • Do we recover training features?