Local Linear Approximation for Kernel Methods: The Railway Kernel. - Alberto Muñoz; Javier González 002; Isaac Martín de Diego (CIARP, 2006)

Joint Diagonalization of Kernels for Information Fusion. - Alberto Muñoz; Javier González 002 (CIARP, 2007)

Spectral Measures for Kernel Matrices Comparison. - Javier González 002; Alberto Muñoz (ICANN (1), 2007)

Functional Learning of Kernels for Information Fusion Purposes. - Alberto Muñoz; Javier González 002 (CIARP, 2008)

Combining Functional Data Projections for Time Series Classification. - Alberto Muñoz; Javier González 002 (CIARP, 2009)

Representing functional data using support vector machines. - Alberto Muñoz; Javier González 002 (Pattern Recognit. Lett., 2010)

On the Generalization of the Mahalanobis Distance. - Gabriel Martos; Alberto Muñoz; Javier González 002 (CIARP (1), 2013)

A New Distance for Data Sets in a Reproducing Kernel Hilbert Space Context. - Alberto Muñoz; Gabriel Martos; Javier González 002 (CIARP (1), 2013)

Functional analysis techniques to improve similarity matrices in discrimination problems. - Javier González 002; Alberto Muñoz (J. Multivar. Anal., 2013)

Generalizing the Mahalanobis distance via density kernels. - Gabriel Martos; Alberto Muñoz; Javier González 002 (Intell. Data Anal., 2014)

Reproducing kernel Hilbert space based estimation of systems of ordinary differential equations. - Javier González 002; Ivan Vujacic; Ernst Wit (Pattern Recognit. Lett., 2014)

Time-course window estimator for ordinary differential equations linear in the parameters. - Ivan Vujacic; Itai Dattner; Javier González 002; Ernst Wit (Stat. Comput., 2015)

Batch Bayesian Optimization via Local Penalization. - Javier González 002; Zhenwen Dai; Philipp Hennig; Neil D. Lawrence (AISTATS, 2016)

GLASSES: Relieving The Myopia Of Bayesian Optimisation. - Javier González 002; Michael A. Osborne; Neil D. Lawrence (AISTATS, 2016)

Variational Auto-encoded Deep Gaussian Processes. - Zhenwen Dai; Andreas C. Damianou; Javier González 002; Neil D. Lawrence (ICLR (Poster), 2016)

Asymmetric latent semantic indexing for gene expression experiments visualization. - Javier González 002; Alberto Muñoz; Gabriel Martos (J. Bioinform. Comput. Biol., 2016)

Preferential Bayesian Optimization. - Javier González 002; Zhenwen Dai; Andreas C. Damianou; Neil D. Lawrence (ICML, 2017)

Bayesian Optimization with Tree-structured Dependencies. - Rodolphe Jenatton; Cédric Archambeau; Javier González 002; Matthias W. Seeger (ICML, 2017)

Structured Variationally Auto-encoded Optimization. - Xiaoyu Lu; Javier González 002; Zhenwen Dai; Neil D. Lawrence (ICML, 2018)

Correcting boundary over-Exploration Deficiencies in Bayesian Optimization with Virtual derivative Sign observations. - Eero Siivola; Aki Vehtari; Jarno Vanhatalo; Javier González 002; Michael Riis Andersen (MLSP, 2018)

Meta-Surrogate Benchmarking for Hyperparameter Optimization. - Aaron Klein; Zhenwen Dai; Frank Hutter; Neil D. Lawrence; Javier González 002 (NeurIPS, 2019)

Deep Gaussian Processes for Multi-fidelity Modeling. - Kurt Cutajar; Mark Pullin; Andreas C. Damianou; Neil D. Lawrence; Javier González 002 (CoRR, 2019)

Causal Bayesian Optimization. - Virginia Aglietti; Xiaoyu Lu; Andrei Paleyes; Javier González 002 (AISTATS, 2020)

BOFFIN TTS: Few-Shot Speaker Adaptation by Bayesian Optimization. - Henry B. Moss; Vatsal Aggarwal; Nishant Prateek; Javier González 002; Roberto Barra-Chicote (ICASSP, 2020)

Multi-task Causal Learning with Gaussian Processes. - Virginia Aglietti; Theodoros Damoulas; Mauricio A. Álvarez; Javier González 002 (NeurIPS, 2020)

Bandit optimisation of functions in the Matérn kernel RKHS. - David Janz; David R. Burt; Javier González 002 (CoRR, 2020)

Learning Inconsistent Preferences with Kernel Methods. - Siu Lun Chau; Javier González 002; Dino Sejdinovic (CoRR, 2020)

Structure Mapping for Transferability of Causal Models. - Purva Pruthi; Javier González 002; Xiaoyu Lu; Madalina Fiterau (CoRR, 2020)

Good practices for Bayesian Optimization of high dimensional structured spaces. - Eero Siivola; Javier González 002; Andrei Paleyes; Aki Vehtari (CoRR, 2020)

Automatic Discovery of Privacy-Utility Pareto Fronts. - Brendan Avent; Javier González 002; Tom Diethe; Andrei Paleyes; Borja Balle (Proc. Priv. Enhancing Technol., 2020)

Preferential Batch Bayesian Optimization. - Eero Siivola; Akash Kumar Dhaka; Michael Riis Andersen; Javier González 002; Pablo Garcia Moreno; Aki Vehtari (MLSP, 2021)

Dynamic Causal Bayesian Optimization. - Virginia Aglietti; Neil Dhir; Javier González 002; Theodoros Damoulas (NeurIPS, 2021)

BayesIMP: Uncertainty Quantification for Causal Data Fusion. - Siu Lun Chau; Jean-Francois Ton; Javier González 002; Yee Whye Teh; Dino Sejdinovic (NeurIPS, 2021)

RKHS-SHAP: Shapley Values for Kernel Methods. - Siu Lun Chau; Javier González 002; Dino Sejdinovic (CoRR, 2021)

Emulation of physical processes with Emukit. - Andrei Paleyes; Mark Pullin; Maren Mahsereci; Cliff McCollum; Neil D. Lawrence; Javier González 002 (CoRR, 2021)

Learning Inconsistent Preferences with Gaussian Processes. - Siu Lun Chau; Javier González 002; Dino Sejdinovic (AISTATS, 2022)

RKHS-SHAP: Shapley Values for Kernel Methods. - Siu Lun Chau; Robert Hu; Javier González 002; Dino Sejdinovic (NeurIPS, 2022)

Beyond Words: A Mathematical Framework for Interpreting Large Language Models. - Javier González 002; Aditya V. Nori (CoRR, 2023)

Cautionary Tales on Synthetic Controls in Survival Analyses. - Alicia Curth; Hoifung Poon; Aditya V. Nori; Javier González 002 (CLeaR, 2024)

Does Reasoning Emerge? Examining the Probabilities of Causation in Large Language Models. - Javier González 002; Aditya V. Nori (CoRR, 2024)

Reasoning Elicitation in Language Models via Counterfactual Feedback. - Alihan Hüyük; Xinnuo Xu; Jacqueline R. M. A. Maasch; Aditya V. Nori; Javier González 002 (ICLR, 2025)

Compositional Causal Reasoning Evaluation in Language Models. - Jacqueline R. M. A. Maasch; Alihan Hüyük; Xinnuo Xu; Aditya V. Nori; Javier González 002 (CoRR, 2025)