3 papers
cs.LG2026
LeMat-GenBench: A Unified Evaluation Framework for Crystal Generative Models
Siddharth Betala, Samuel P. Gleason, Ali Ramlaoui +12
Generative machine learning (ML) models hold great promise for accelerating materials discovery through the inverse design of inorganic crystals, enabling an unprecedented explorat…
cs.LG2025
Transformers are Graph Neural Networks
Chaitanya K. Joshi
We establish connections between the Transformer architecture, originally introduced for natural language processing, and Graph Neural Networks (GNNs) for representation learning o…
cs.LG2025
All-atom Diffusion Transformers: Unified generative modelling of molecules and materials
Chaitanya K. Joshi, Xiang Fu, Yi-Lun Liao +4
Diffusion models are the standard toolkit for generative modelling of 3D atomic systems. However, for different types of atomic systems -- such as molecules and materials -- the ge…