Probabilistic graph-to-graph model for reaction prediction and retrosynthetic route prediction
Lead Research Organisation:
UNIVERSITY OF CAMBRIDGE
Department Name: Engineering
Abstract
This project aims to develop machine learning methodologies that predict the outcomes of chemical reaction given reagent and reactant. We also aim solve the inverse problem of devising a sequence of reactions to make a target compound from simple starting materials.
People |
ORCID iD |
| Gabor Csanyi (Primary Supervisor) | |
| David Kovacs (Student) |
Publications
Kovács DP
(2021)
Linear Atomic Cluster Expansion Force Fields for Organic Molecules: Beyond RMSE.
in Journal of chemical theory and computation
Kovács DP
(2021)
Quantitative interpretation explains machine learning models for chemical reaction prediction and uncovers bias.
in Nature communications
Kovács D
(2024)
Machine Learning Force Fields for Molecular Chemistry
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| EP/T517677/1 | 30/09/2019 | 29/09/2025 | |||
| 2276922 | Studentship | EP/T517677/1 | 30/09/2019 | 07/12/2023 | David Kovacs |