González, Javier

27 publications

CLeaR 2025 Beyond Flatland: A Geometric Take on Matching Methods for Treatment Effect Estimation Melanie F. Pradier, Javier González

ICML 2025 Compositional Causal Reasoning Evaluation in Language Models Jacqueline R. M. A. Maasch, Alihan Hüyük, Xinnuo Xu, Aditya V. Nori, Javier Gonzalez

ICML 2025 RE-IMAGINE: Symbolic Benchmark Synthesis for Reasoning Evaluation Xinnuo Xu, Rachel Lawrence, Kshitij Dubey, Atharva Pandey, Risa Ueno, Fabian Falck, Aditya V. Nori, Rahul Sharma, Amit Sharma, Javier Gonzalez

ICLRW 2025 Re-Imagine: Symbolic Benchmark Synthesis for Reasoning Evaluation Xinnuo Xu, Rachel Lawrence, Kshitij Dubey, Atharva Pandey, Fabian Falck, Risa Ueno, Aditya V. Nori, Rahul Sharma, Amit Sharma, Javier Gonzalez

ICLR 2025 Reasoning Elicitation in Language Models via Counterfactual Feedback Alihan Hüyük, Xinnuo Xu, Jacqueline R. M. A. Maasch, Aditya V. Nori, Javier Gonzalez

CLeaR 2024 Cautionary Tales on Synthetic Controls in Survival Analyses Alicia Curth, Hoifung Poon, Aditya V. Nori, Javier González

NeurIPS 2024 Does Reasoning Emerge? Examining the Probabilities of Causation in Large Language Models Javier González, Aditya V. Nori

ICML 2024 Safe Exploration in Dose Finding Clinical Trials with Heterogeneous Participants Isabel Chien, Wessel P Bruinsma, Javier Gonzalez, Richard E. Turner

AISTATS 2022 Learning Inconsistent Preferences with Gaussian Processes Siu Lun Chau, Javier Gonzalez, Dino Sejdinovic

AISTATS 2022 Predicting the Impact of Treatments over Time with Uncertainty Aware Neural Differential Equations. Edward De Brouwer, Javier Gonzalez, Stephanie Hyland

NeurIPS 2022 RKHS-SHAP: Shapley Values for Kernel Methods Siu Lun Chau, Robert Hu, Javier González, Dino Sejdinovic

NeurIPS 2021 BayesIMP: Uncertainty Quantification for Causal Data Fusion Siu Lun Chau, Jean-Francois Ton, Javier González, Yee W. Teh, Dino Sejdinovic

NeurIPS 2021 Dynamic Causal Bayesian Optimization Virginia Aglietti, Neil Dhir, Javier González, Theodoros Damoulas

JMLR 2021 GIBBON: General-Purpose Information-Based Bayesian Optimisation Henry B. Moss, David S. Leslie, Javier Gonzalez, Paul Rayson

ICML 2020 BINOCULARS for Efficient, Nonmyopic Sequential Experimental Design Shali Jiang, Henry Chai, Javier Gonzalez, Roman Garnett

NeurIPS 2020 BOSS: Bayesian Optimization over String Spaces Henry Moss, David Leslie, Daniel Beck, Javier González, Paul Rayson

AISTATS 2020 Bandit Optimisation of Functions in the Matérn Kernel RKHS David Janz, David Burt, Javier Gonzalez

AISTATS 2020 Causal Bayesian Optimization Virginia Aglietti, Xiaoyu Lu, Andrei Paleyes, Javier González

NeurIPS 2020 Multi-Task Causal Learning with Gaussian Processes Virginia Aglietti, Theodoros Damoulas, Mauricio Álvarez, Javier González

UAI 2019 Active Multi-Information Source Bayesian Quadrature Alexandra Gessner, Javier Gonzalez, Maren Mahsereci

NeurIPS 2019 Meta-Surrogate Benchmarking for Hyperparameter Optimization Aaron Klein, Zhenwen Dai, Frank Hutter, Neil Lawrence, Javier Gonzalez

ICML 2018 Structured Variationally Auto-Encoded Optimization Xiaoyu Lu, Javier Gonzalez, Zhenwen Dai, Neil D. Lawrence

ICML 2017 Bayesian Optimization with Tree-Structured Dependencies Rodolphe Jenatton, Cedric Archambeau, Javier González, Matthias Seeger

ICML 2017 Preferential Bayesian Optimization Javier González, Zhenwen Dai, Andreas Damianou, Neil D. Lawrence

AISTATS 2016 Batch Bayesian Optimization via Local Penalization Javier González, Zhenwen Dai, Philipp Hennig, Neil D. Lawrence

AISTATS 2016 GLASSES: Relieving the Myopia of Bayesian Optimisation Javier González, Michael A. Osborne, Neil D. Lawrence

ICLR 2016 Variational Auto-Encoded Deep Gaussian Processes Zhenwen Dai, Andreas C. Damianou, Javier González, Neil D. Lawrence