Portrait of Danyal REHMAN is unavailable

Danyal REHMAN

Postdoctorate - Université de Montréal
Supervisor
Yoshua Bengio
Research Topics
Deep Learning
Generative Models
Molecular Modeling
Reinforcement Learning
Representation Learning
GitHub

Publications

FALCON: Few-step Accurate Likelihoods for Continuous Flows
Danyal REHMAN
Tara Akhound-Sadegh
Artem Gazizov
Yoshua Bengio
Alexander Tong
2025-11-30
arXiv (published)
doi.org
arxiv.org
Efficient Regression-Based Training of Normalizing Flows for Boltzmann Generators
Danyal REHMAN
Oscar Davis
Jiarui Lu
Jian Tang
Michael Bronstein
Yoshua Bengio
Alexander Tong
Avishek Joey Bose
Simulation-free training frameworks have been at the forefront of the generative modelling revolution in continuous spaces, leading to large… (see more)-scale diffusion and flow matching models. However, such modern generative models suffer from expensive inference, inhibiting their use in numerous scientific applications like Boltzmann Generators (BGs) for molecular conformations that require fast likelihood evaluation. In this paper, we revisit classical normalizing flows in the context of BGs that offer efficient sampling and likelihoods, but whose training via maximum likelihood is often unstable and computationally challenging. We propose Regression Training of Normalizing Flows (RegFlow), a novel and scalable regression-based training objective that bypasses the numerical instability and computational challenge of conventional maximum likelihood training in favour of a simple
2025-06-10
ICML.cc/2025/Workshop/GenBio (spotlight)
doi.org
openreview.net