4 citations · 9 across the 9 of their papers we have counts for
4 papers · 1 filter
Accelerating Scientific Discovery with Autonomous Goal-evolving Agents
Yuanqi Du, Botao Yu, Tianyu Liu +25
There has been unprecedented interest in developing agents that expand the boundary of scientific discovery, primarily by optimizing quantitative objective functions specified by s…
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…
Compositional Flows for 3D Molecule and Synthesis Pathway Co-design
Tony Shen, Seonghwan Seo, Ross Irwin +4
Many generative applications, such as synthesis-based 3D molecular design, involve constructing compositional objects with continuous features. Here, we introduce Compositional Gen…
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…