2 citations · 2 across the 2 of their papers we have counts for
3 papers · 1 filter
Score-based Idempotent Distillation of Diffusion Models
Shehtab Zaman, Chengyan Liu, Kenneth Chiu
Idempotent generative networks (IGNs) are a new line of generative models based on idempotent mapping to a target manifold. IGNs support both single-and multi-step generation, allo…
BOOM: Benchmarking Out-Of-distribution Molecular Property Predictions of Machine Learning Models
Evan R. Antoniuk, Shehtab Zaman, Tal Ben-Nun +9
Data-driven molecular discovery leverages artificial intelligence/machine learning (AI/ML) and generative modeling to filter and design novel molecules. Discovering novel molecules…
Distributed Reinforcement Learning for Molecular Design: Antioxidant case
Huanyi Qin, Denis Akhiyarov, Sophie Loehle +2
Deep reinforcement learning has successfully been applied for molecular discovery as shown by the Molecule Deep Q-network (MolDQN) algorithm. This algorithm has challenges when app…