José Jiménez-Luna

According to our database, José Jiménez-Luna authored at least 8 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Enhanced Diffusion Sampling: Efficient Rare Event Sampling and Free Energy Calculation with Diffusion Models.

Yu Xie, Ludwig Winkler, Lixin Sun, Sarah Lewis, Adam Evan Foster, José Jiménez-Luna, Tim Hempel, Michael Gastegger, Yaoyi Chen, Iryna Zaporozhets, Cecilia Clementi, Christopher M. Bishop, Frank Noé

CoRR, February, 2026

2024

Improved motif-scaffolding with SE(3) flow matching.

Jason Yim, Andrew Campbell, Emile Mathieu, Andrew Y. K. Foong, Michael Gastegger, José Jiménez-Luna, Sarah Lewis, Victor Garcia Satorras, Bastiaan S. Veeling, Frank Noé, Regina Barzilay, Tommi S. Jaakkola

Trans. Mach. Learn. Res., 2024

2023

Explaining compound activity predictions with a substructure-aware loss for graph neural networks.

Kenza Amara, Raquel Rodríguez-Pérez, José Jiménez-Luna

J. Cheminformatics, December, 2023

2022

PlayMolecule Glimpse: Understanding Protein-Ligand Property Predictions with Interpretable Neural Networks.

Alejandro Varela-Rial, Iain Maryanow, Maciej Majewski, Stefan Doerr, Nikolai Schapin, José Jiménez-Luna, Gianni De Fabritiis

J. Chem. Inf. Model., 2022

Benchmarking Molecular Feature Attribution Methods with Activity Cliffs.

José Jiménez-Luna, Miha Skalic, Nils Weskamp

J. Chem. Inf. Model., 2022

Structure-based drug discovery with deep learning.

Riza Özçelik, Derek van Tilborg, José Jiménez-Luna, Francesca Grisoni

CoRR, 2022

2021

Coloring Molecules with Explainable Artificial Intelligence for Preclinical Relevance Assessment.

José Jiménez-Luna, Miha Skalic, Nils Weskamp, Gisbert Schneider

J. Chem. Inf. Model., 2021

2020

Drug discovery with explainable artificial intelligence.

José Jiménez-Luna, Francesca Grisoni, Gisbert Schneider

Nat. Mach. Intell., 2020