4 papers
From Knowledge to Action: Outcomes of the 2025 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry
Aritra Roy, Kevin Shen, Andrew MacBride +350
Large language models (LLMs) are rapidly changing how researchers in materials science and chemistry discover, organize, and act on scientific knowledge. This paper analyzes a broa…
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…
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…
PtychoFormer: A Transformer-based Model for Ptychographic Phase Retrieval
Ryuma Nakahata, Shehtab Zaman, Mingyuan Zhang +2
Ptychography is a computational method of microscopy that recovers high-resolution transmission images of samples from a series of diffraction patterns. While conventional phase re…