Cesar de la Fuente-Nunez

According to our database, Cesar de la Fuente-Nunez authored at least 13 papers between 2023 and 2026.

Collaborative distances:

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

2026

Self-Driving Datasets: From 20 Million Papers to Nuanced Biomedical Knowledge at Scale.

Haydn Thomas Jones, Yimeng Zeng, Alden Rose, Li S. Yifei, Yining Huang, Kaiwen Wu, Jiaming Liang, Maggie Ziyu Huan, Yoseph Barash, Cesar de la Fuente-Nunez, Osbert Bastani, Zachary G. Ives, Mark Yatskar, Jacob R. Gardner

CoRR, May, 2026

Purely Agentic Black-Box Optimization for Biological Design.

Natalie Maus, Yimeng Zeng, Haydn Thomas Jones, Yining Huang, Gaurav Ng Goel, Alden Rose, Kyurae Kim, Hyun-Su Lee, Marcelo Der Torossian Torres, Fangping Wan, Cesar de la Fuente-Nunez, Mark Yatskar, Osbert Bastani, Jacob R. Gardner

CoRR, January, 2026

2025

PepCompass: Navigating peptide embedding spaces using Riemannian Geometry.

Marcin Mozejko, Adam Bielecki, Jurand Pradzynski, Marcin Traskowski, Antoni Janowski, Hyun-Su Lee, Marcelo Der Torossian Torres, Michal Kmicikiewicz, Paulina Szymczak, Karol Jurasz, Michal Kucharczyk, Cesar de la Fuente-Nunez, Ewa Szczurek

CoRR, October, 2025

From Supervision to Exploration: What Does Protein Language Model Learn During Reinforcement Learning?

Hanqun Cao, Hongrui Zhang, Junde Xu, Zhou Zhang, Lingdong Shen, Minghao Sun, Ge Liu, Jinbo Xu, Wu-Jun Li, Jinren Ni, Cesar de la Fuente-Nunez, Tianfan Fu, Yejin Choi, Pheng-Ann Heng, Fang Wu

CoRR, October, 2025

A deep reinforcement learning platform for antibiotic discovery.

Hanqun Cao, Marcelo Der Torossian Torres, Jingjie Zhang, Zijun Gao, Fang Wu, Chunbin Gu, Jure Leskovec, Yejin Choi, Cesar de la Fuente-Nunez, Guangyong Chen, Pheng-Ann Heng

CoRR, September, 2025

A Dataset for Distilling Knowledge Priors from Literature for Therapeutic Design.

Haydn Thomas Jones, Natalie Maus, Josh Magnus Ludan, Maggie Ziyu Huan, Jiaming Liang, Marcelo Der Torossian Torres, Jiatao Liang, Zachary G. Ives, Yoseph Barash, Cesar de la Fuente-Nunez, Jacob R. Gardner, Mark Yatskar

CoRR, August, 2025

Predicting and generating antibiotics against future pathogens with ApexOracle.

Tianang Leng, Fangping Wan, Marcelo Der Torossian Torres, Cesar de la Fuente-Nunez

CoRR, July, 2025

Large Scale Multi-Task Bayesian Optimization with Large Language Models.

Yimeng Zeng, Natalie Maus, Haydn Thomas Jones, Jeffrey Tao, Fangping Wan, Marcelo Der Torossian Torres, Cesar de la Fuente-Nunez, Ryan Marcus, Osbert Bastani, Jacob R. Gardner

CoRR, March, 2025

Covering Multiple Objectives with a Small Set of Solutions Using Bayesian Optimization.

Natalie Maus, Kyurae Kim, Yimeng Zeng, Haydn Thomas Jones, Fangping Wan, Marcelo Der Torossian Torres, Cesar de la Fuente-Nunez, Jacob R. Gardner

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

2024

From Data to Decisions: Leveraging Artificial Intelligence and Machine Learning in Combating Antimicrobial Resistance - a Comprehensive Review.

José M. Pérez de la Lastra, Samuel J. T. Wardell, Tarun Pal, Cesar de la Fuente-Nunez, Daniel Pletzer

J. Medical Syst., December, 2024

AI in biomaterials discovery: generating self-assembling peptides with resource-efficient deep learning.

Tianang Leng, Cesar de la Fuente-Nunez

Nat. Mac. Intell., 2024

Editorial: Machine learning approaches to antimicrobials: discovery and resistance.

Shira L. Broschat, Shirley W. I. Siu, Cesar de la Fuente-Nunez

Frontiers Bioinform., 2024

2023

Geometric deep learning as a potential tool for antimicrobial peptide prediction.

Fabiano C. Fernandes, Marlon H. Cardoso, Abel Gil-Ley, Lívia V. Luchi, Maria G. L. da Silva, Maria L. R. Macedo, Cesar de la Fuente-Nunez, Octávio L. Franco

Frontiers Bioinform., May, 2023