From the 1 of 3 linked papers with an AI index.
1 citations · 1 across the 2 of their papers we have counts for
3 papers
How Molecular Generative Models Organize Molecular Identity
Raul Ortega-Ochoa, Tejs Vegge, Jens S. Bakander +3
Generative models for matter are often evaluated as samplers over output representations, and their latent spaces are commonly used as proxies for navigating chemical space. Much l…
MolMiner: Toward Controllable, 3D-Aware, Fragment-Based Molecular Design
Raul Ortega-Ochoa, Tejs Vegge, Jes Frellsen
MolMiner is an autoregressive model that builds molecules by attaching fragments in a geometry‑aware, symmetry‑respecting way, while allowing users to control multiple physicochemi…
A tomographic interpretation of structure-property relations for materials discovery
Raul Ortega-Ochoa, Alán Aspuru-Guzik, Tejs Vegge +1
Recent advancements in machine learning (ML) for materials have demonstrated that "simple" materials representations (e.g., the chemical formula alone without structural informatio…