1 citations · 1 across the 3 of their papers we have counts for
3 papers
A Modular Agentic Framework for Synthetically Constrained Multi-Objective Hit-to-Lead Optimization
Kelvin P. Idanwekhai, Enes Kelestemur, Benjamin Strickland +6
Hit-to-lead optimization requires iterative design of hit analogs across competing potency, selectivity, physicochemical, pharmacokinetic, safety, and synthetic constraints. We pre…
BASIL: Bayesian Application for Scientific Iteration and Learning
Kelvin P. Idanwekhai, Valeriia Kaneva, Stefano Menegatti +1
We introduce BASIL, a user-friendly desktop application for process optimization. BASIL employs a Bayesian approach, incorporating special acquisition functions that can be used to…
On Graph Neural Network Ensembles for Large-Scale Molecular Property Prediction
Edward Elson Kosasih, Joaquin Cabezas, Xavier Sumba +5
In order to advance large-scale graph machine learning, the Open Graph Benchmark Large Scale Challenge (OGB-LSC) was proposed at the KDD Cup 2021. The PCQM4M-LSC dataset defines a…