2 citations · 4 across the 6 of their papers we have counts for
6 papers
Why Pool When You Can Flow? Active Learning with GFlowNets
Renfei Zhang, Mohit Pandey, Artem Cherkasov +1
The scalability of pool-based active learning is limited by the computational cost of evaluating large unlabeled datasets, a challenge that is particularly acute in virtual screeni…
Biomarker Integration and Biosensor Technologies Enabling AI-Driven Insights into Biological Aging
Jared A Kushner, Mohit Pandey, Sandeep +1
As the global population continues to age, there is an increasing demand for ways to accurately quantify the biological processes underlying aging. Biological age, unlike chronolog…
Pretraining Generative Flow Networks with Inexpensive Rewards for Molecular Graph Generation
Mohit Pandey, Gopeshh Subbaraj, Artem Cherkasov +2
Generative Flow Networks (GFlowNets) have recently emerged as a suitable framework for generating diverse and high-quality molecular structures by learning from rewards treated as…
GFlowNet Pretraining with Inexpensive Rewards
Mohit Pandey, Gopeshh Subbaraj, Emmanuel Bengio
Generative Flow Networks (GFlowNets), a class of generative models have recently emerged as a suitable framework for generating diverse and high-quality molecular structures by lea…
TacoGFN: Target-conditioned GFlowNet for Structure-based Drug Design
Tony Shen, Seonghwan Seo, Grayson Lee +5
Searching the vast chemical space for drug-like molecules that bind with a protein pocket is a challenging task in drug discovery. Recently, structure-based generative models have…
Multibody molecular docking on a quantum annealer
Mohit Pandey, Tristan Zaborniak, Hans Melo +2
Molecular docking, which aims to find the most stable interacting configuration of a set of molecules, is of critical importance to drug discovery. Although a considerable number o…