2 citations · 2 across the 3 of their papers we have counts for
5 papers
Mixture of GFlowNets
Omar G. Younis, Joseph D. Viviano, Chirayu Anant Haryan +3
Generative Flow Networks (GFlowNets) learn a policy that samples compositional objects in proportion to an unnormalized reward . This makes them useful wherever many diverse,…
Multi-Objective Amortized CDRH3 Sequence Sampling Diversifies Promising Antibody Candidates
Joseph D. Viviano, Almer van der Sloot, Quentin Fournier +3
Antibody therapeutics have transformed treatment across diverse therapeutic areas and have become central to modern medicine. While recent machine learning approaches aim to accele…
Local Inconsistency Resolution: The Interplay between Attention and Control in Probabilistic Models
Oliver E. Richardson, Mandana Samiei, Mehran Shakerinava +4
We present a generic algorithm for learning and approximate inference with an intuitive epistemic interpretation: iteratively focus on a subset of the model and resolve inconsisten…
A scalable gene network model of regulatory dynamics in single cells
Paul Bertin, Joseph D. Viviano, Alejandro Tejada-Lapuerta +4
Single-cell data provide high-dimensional measurements of the transcriptional states of cells, but extracting insights into the regulatory functions of genes, particularly identify…
Action abstractions for amortized sampling
Oussama Boussif, Léna Néhale Ezzine, Joseph D Viviano +6
As trajectories sampled by policies used by reinforcement learning (RL) and generative flow networks (GFlowNets) grow longer, credit assignment and exploration become more challeng…