3 citations · 5 across the 7 of their papers we have counts for
4 papers · 1 filter
Vector Field Oriented Diffusion Model for Crystal Material Generation
Astrid Klipfel, Yaël Fregier, Adlane Sayede +1
Discovering crystal structures with specific chemical properties has become an increasingly important focus in material science. However, current models are limited in their abilit…
Optimized Crystallographic Graph Generation for Material Science
Astrid Klipfel, Yaël Frégier, Adlane Sayede +1
Graph neural networks are widely used in machine learning applied to chemistry, and in particular for material science discovery. For crystalline materials, however, generating gra…
Unified Model for Crystalline Material Generation
Astrid Klipfel, Yaël Frégier, Adlane Sayede +1
One of the greatest challenges facing our society is the discovery of new innovative crystal materials with specific properties. Recently, the problem of generating crystal materia…
Equivariant Message Passing Neural Network for Crystal Material Discovery
Astrid Klipfel, Olivier Peltre, Najwa Harrati +3
Automatic material discovery with desired properties is a fundamental challenge for material sciences. Considerable attention has recently been devoted to generating stable crystal…