4 papers
Atom-JEPA: Joint-Embedding Predictive Architecture for 3D Atomistic Systems
Kasper Helverskov Petersen, Rasmus Hannibal Tirsgaard, François R J Cornet +2
Large-scale self-supervised pretraining has reshaped modern machine learning, substantially advancing the ability of language and vision models to generalize across downstream task…
Equivariant Graph Neural Networks Improve Optical Spectra Prediction for Materials Screening
Kasper Helverskov Petersen, François R J Cornet, Martin Ovesen +3
Scalable prediction of optical spectra is a critical component of high-throughput materials screening for optoelectronic applications such as solar cells. Existing surrogate models…
AtomComposer: Discovering Chemical Space from First Principles with Reinforcement Learning
Bjarke Hastrup, Francois Cornet, Tejs Vegge +1
Discovering novel stable molecules without training data remains a grand scientific challenge. Current molecular generative models are trained on large, pre-curated datasets, which…
Equivariant Neural Diffusion for Molecule Generation
François Cornet, Grigory Bartosh, Mikkel N. Schmidt +1
We introduce Equivariant Neural Diffusion (END), a novel diffusion model for molecule generation in 3D that is equivariant to Euclidean transformations. Compared to current state-o…