Cotta, Leonardo

11 publications

TMLR 2026 Bayesian Sensitivity of Causal Inference Estimators Under Evidence-Based Priors Nikita Dhawan, Daniel Shen, Leonardo Cotta, Chris J. Maddison

NeurIPS 2025 Measuring Scientific Capabilities of Language Models with a Systems Biology Dry Lab Haonan Duan, Stephen Zhewen Lu, Caitlin Fiona Harrigan, Nishkrit Desai, Jiarui Lu, Michał Koziarski, Leonardo Cotta, Chris J. Maddison

TMLR 2025 Test-Time Fairness and Robustness in Large Language Models Leonardo Cotta, Chris J. Maddison

NeurIPS 2024 End-to-End Causal Effect Estimation from Unstructured Natural Language Data Nikita Dhawan, Leonardo Cotta, Karen Ullrich, Rahul G. Krishnan, Chris J. Maddison

ICMLW 2024 End-to-End Causal Effect Estimation from Unstructured Natural Language Data Nikita Dhawan, Leonardo Cotta, Karen Ullrich, Rahul Krishnan, Chris J. Maddison

ICMLW 2024 Out-of-Context Prompting Boosts Fairness and Robustness in Large Language Model Predictions Leonardo Cotta, Chris J. Maddison

ICMLW 2024 PAIR: Boosting the Predictive Power of Protein Representations with a Corpus of Text Annotations Haonan Duan, Marta Skreta, Leonardo Cotta, Ella Miray Rajaonson, Nikita Dhawan, Alan Aspuru-Guzik, Chris J. Maddison

NeurIPS 2023 Probabilistic Invariant Learning with Randomized Linear Classifiers Leonardo Cotta, Gal Yehuda, Assaf Schuster, Chris J Maddison

LoG 2022 The First Learning on Graphs Conference: Preface Bastian Rieck, Razvan Pascanu, Yuanqi Du, Hannes Stärk, Derek Lim, Chaitanya K. Joshi, Andreea Deac, Iulia Duta, Joshua Robinson, Gabriele Corso, Leonardo Cotta, Yanqiao Zhu, Kexin Huang, Michelle Li, Sofia Bourhim, Ilia Igashov

NeurIPS 2021 Reconstruction for Powerful Graph Representations Leonardo Cotta, Christopher Morris, Bruno Ribeiro

NeurIPS 2020 Unsupervised Joint K-Node Graph Representations with Compositional Energy-Based Models Leonardo Cotta, Carlos H. C. Teixeira, Ananthram Swami, Bruno Ribeiro