Learning optimal environments using projected stochastic gradient ascent. - Adrien Bolland; Ioannis Boukas; François R. J. Cornet; Mathias Berger; Damien Ernst (CoRR, 2020)

Equivariant Neural Diffusion for Molecule Generation. - François R. J. Cornet; Grigory Bartosh; Mikkel N. Schmidt; Christian Andersson Naesseth (NeurIPS, 2024)

Kinetic Langevin Diffusion for Crystalline Materials Generation. - François R. J. Cornet; Federico Bergamin; Arghya Bhowmik; Juan Maria Garcia Lastra; Jes Frellsen; Mikkel N. Schmidt (ICML, 2025)

Improving generative inverse design of molecular catalysts in small data regime. - François R. J. Cornet; Pratham Deshmukh; Bardi Benediktsson; Mikkel N. Schmidt; Arghya Bhowmik (Mach. Learn. Sci. Technol., 2025)

AtomComposer: Discovering Chemical Space from First Principles with Reinforcement Learning. - Bjarke Hastrup; François R. J. Cornet; Tejs Vegge; Arghya Bhowmik (CoRR, 2026)