The exploration of transition state (TS) geometries is crucial for elucidating chemical reaction mechanisms and modeling their kinetics.
Hence, to incorporate information of the correct, GeoTMI aims to maximize mutual information between three variables: the correct and the corrupted geometries and the property.
This challenge, on the other hand, is interested in the exploration capability of MARL algorithms to efficiently learn implicit multi-stage tasks and environmental factors as well as micro-control.
Ranked #1 on SMAC+ on Off_Superhard_parallel
In a restricted computing environment like satellite on-board systems, running DL models has limitation on high-speed processing due to the problems such as restriction of available power to consume compared to the relatively high computational complexity.