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Javier González 0002
Person information
- affiliation: Microsoft Research Cambridge
- affiliation (former): Amazon
- affiliation (former): University of Sheffield, UK
- affiliation (former): Universidad Carlos III de Madrid, Spain
Other persons with the same name
- Javier González — disambiguation page
- Javier González 0001
(aka: Javier Gonzalez 0001, Javier González Jiménez 0001) — University of Málaga, Spain
- Javier González 0003 — Universidad Panamericana, Mexico
- Javier González 0004 — Universitat de Barcelona i Parc Científic de Barcelona, Spain
- Javier González 0005 — Center for Remote Sensing of Land Surfaces (ZFL), University of Bonn, Bonn, Germany
- Javier González 0006 — Samsung, Copenhagen, Denmark (and 1 more)
- Javier González 0007 — University of Burgos, Spain
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2020 – today
- 2024
- [c25]Alicia Curth, Hoifung Poon, Aditya V. Nori, Javier González:
Cautionary Tales on Synthetic Controls in Survival Analyses. CLeaR 2024: 143-159 - [i18]Javier González, Aditya V. Nori:
Does Reasoning Emerge? Examining the Probabilities of Causation in Large Language Models. CoRR abs/2408.08210 (2024) - [i17]Alihan Hüyük, Xinnuo Xu, Jacqueline Maasch, Aditya V. Nori, Javier González:
Reasoning Elicitation in Language Models via Counterfactual Feedback. CoRR abs/2410.03767 (2024) - 2023
- [i16]Javier González, Aditya V. Nori:
Beyond Words: A Mathematical Framework for Interpreting Large Language Models. CoRR abs/2311.03033 (2023) - 2022
- [c24]Siu Lun Chau, Javier González, Dino Sejdinovic:
Learning Inconsistent Preferences with Gaussian Processes. AISTATS 2022: 2266-2281 - [c23]Siu Lun Chau, Robert Hu, Javier González, Dino Sejdinovic:
RKHS-SHAP: Shapley Values for Kernel Methods. NeurIPS 2022 - 2021
- [c22]Eero Siivola
Preferential Batch Bayesian Optimization. MLSP 2021: 1-6 - [c21]Siu Lun Chau, Jean-Francois Ton, Javier González, Yee Whye Teh, Dino Sejdinovic:
BayesIMP: Uncertainty Quantification for Causal Data Fusion. NeurIPS 2021: 3466-3477 - [c20]Virginia Aglietti, Neil Dhir, Javier González, Theodoros Damoulas:
Dynamic Causal Bayesian Optimization. NeurIPS 2021: 10549-10560 - [i15]Siu Lun Chau, Jean-François Ton, Javier González, Yee Whye Teh, Dino Sejdinovic:
BayesIMP: Uncertainty Quantification for Causal Data Fusion. CoRR abs/2106.03477 (2021) - [i14]Siu Lun Chau, Javier González, Dino Sejdinovic:
RKHS-SHAP: Shapley Values for Kernel Methods. CoRR abs/2110.09167 (2021) - [i13]Andrei Paleyes, Mark Pullin, Maren Mahsereci, Cliff McCollum, Neil D. Lawrence
Emulation of physical processes with Emukit. CoRR abs/2110.13293 (2021) - [i12]Virginia Aglietti, Neil Dhir, Javier González, Theodoros Damoulas:
Dynamic Causal Bayesian Optimization. CoRR abs/2110.13891 (2021) - 2020
- [j7]Brendan Avent, Javier González, Tom Diethe, Andrei Paleyes
Automatic Discovery of Privacy-Utility Pareto Fronts. Proc. Priv. Enhancing Technol. 2020(4): 5-23 (2020) - [c19]Virginia Aglietti, Xiaoyu Lu, Andrei Paleyes, Javier González:
Causal Bayesian Optimization. AISTATS 2020: 3155-3164 - [c18]Henry B. Moss, Vatsal Aggarwal, Nishant Prateek, Javier González, Roberto Barra-Chicote:
BOFFIN TTS: Few-Shot Speaker Adaptation by Bayesian Optimization. ICASSP 2020: 7639-7643 - [c17]Virginia Aglietti, Theodoros Damoulas, Mauricio A. Álvarez, Javier González:
Multi-task Causal Learning with Gaussian Processes. NeurIPS 2020 - [i11]David Janz, David R. Burt, Javier González:
Bandit optimisation of functions in the Matérn kernel RKHS. CoRR abs/2001.10396 (2020) - [i10]Henry B. Moss, Vatsal Aggarwal, Nishant Prateek, Javier González, Roberto Barra-Chicote:
BOFFIN TTS: Few-Shot Speaker Adaptation by Bayesian Optimization. CoRR abs/2002.01953 (2020) - [i9]Eero Siivola, Akash Kumar Dhaka, Michael Riis Andersen, Javier González, Pablo Garcia Moreno, Aki Vehtari:
Preferential Batch Bayesian Optimization. CoRR abs/2003.11435 (2020) - [i8]Virginia Aglietti, Xiaoyu Lu, Andrei Paleyes, Javier González:
Causal Bayesian Optimization. CoRR abs/2005.11741 (2020) - [i7]Siu Lun Chau, Javier González, Dino Sejdinovic:
Learning Inconsistent Preferences with Kernel Methods. CoRR abs/2006.03847 (2020) - [i6]Purva Pruthi, Javier González, Xiaoyu Lu, Madalina Fiterau:
Structure Mapping for Transferability of Causal Models. CoRR abs/2007.09445 (2020) - [i5]Virginia Aglietti, Theodoros Damoulas, Mauricio A. Álvarez, Javier González:
Multi-task Causal Learning with Gaussian Processes. CoRR abs/2009.12821 (2020) - [i4]Eero Siivola, Javier González, Andrei Paleyes, Aki Vehtari:
Good practices for Bayesian Optimization of high dimensional structured spaces. CoRR abs/2012.15471 (2020)
2010 – 2019
- 2019
- [c16]Aaron Klein, Zhenwen Dai, Frank Hutter, Neil D. Lawrence, Javier González:
Meta-Surrogate Benchmarking for Hyperparameter Optimization. NeurIPS 2019: 6267-6277 - [i3]Kurt Cutajar, Mark Pullin, Andreas C. Damianou, Neil D. Lawrence
Deep Gaussian Processes for Multi-fidelity Modeling. CoRR abs/1903.07320 (2019) - [i2]Brendan Avent, Javier González, Tom Diethe, Andrei Paleyes, Borja Balle:
Automatic Discovery of Privacy-Utility Pareto Fronts. CoRR abs/1905.10862 (2019) - [i1]Aaron Klein, Zhenwen Dai, Frank Hutter, Neil D. Lawrence, Javier González:
Meta-Surrogate Benchmarking for Hyperparameter Optimization. CoRR abs/1905.12982 (2019) - 2018
- [c15]Xiaoyu Lu, Javier González, Zhenwen Dai, Neil D. Lawrence:
Structured Variationally Auto-encoded Optimization. ICML 2018: 3273-3281 - [c14]Eero Siivola
Correcting boundary over-Exploration Deficiencies in Bayesian Optimization with Virtual derivative Sign observations. MLSP 2018: 1-6 - 2017
- [c13]Javier González, Zhenwen Dai, Andreas C. Damianou, Neil D. Lawrence:
Preferential Bayesian Optimization. ICML 2017: 1282-1291 - [c12]Rodolphe Jenatton, Cédric Archambeau, Javier González, Matthias W. Seeger:
Bayesian Optimization with Tree-structured Dependencies. ICML 2017: 1655-1664 - 2016
- [j6]Javier González, Alberto Muñoz
Asymmetric latent semantic indexing for gene expression experiments visualization. J. Bioinform. Comput. Biol. 14(4): 1650023:1-1650023:18 (2016) - [c11]Javier González, Zhenwen Dai, Philipp Hennig, Neil D. Lawrence:
Batch Bayesian Optimization via Local Penalization. AISTATS 2016: 648-657 - [c10]Javier González, Michael A. Osborne, Neil D. Lawrence:
GLASSES: Relieving The Myopia Of Bayesian Optimisation. AISTATS 2016: 790-799 - [c9]Zhenwen Dai, Andreas C. Damianou, Javier González, Neil D. Lawrence
Variational Auto-encoded Deep Gaussian Processes. ICLR (Poster) 2016 - 2015
- [j5]Ivan Vujacic, Itai Dattner, Javier González, Ernst Wit:
Time-course window estimator for ordinary differential equations linear in the parameters. Stat. Comput. 25(6): 1057-1070 (2015) - 2014
- [j4]Gabriel Martos, Alberto Muñoz
Generalizing the Mahalanobis distance via density kernels. Intell. Data Anal. 18(Supplement): S19-S31 (2014) - [j3]Javier González, Ivan Vujacic, Ernst Wit
Reproducing kernel Hilbert space based estimation of systems of ordinary differential equations. Pattern Recognit. Lett. 45: 26-32 (2014) - 2013
- [j2]Javier González, Alberto Muñoz
Functional analysis techniques to improve similarity matrices in discrimination problems. J. Multivar. Anal. 120: 120-134 (2013) - [c8]Gabriel Martos, Alberto Muñoz
On the Generalization of the Mahalanobis Distance. CIARP (1) 2013: 125-132 - [c7]Alberto Muñoz
A New Distance for Data Sets in a Reproducing Kernel Hilbert Space Context. CIARP (1) 2013: 222-229 - 2010
- [j1]Alberto Muñoz
Representing functional data using support vector machines. Pattern Recognit. Lett. 31(6): 511-516 (2010)
2000 – 2009
- 2009
- [c6]Alberto Muñoz
Combining Functional Data Projections for Time Series Classification. CIARP 2009: 457-464 - 2008
- [c5]Alberto Muñoz
Functional Learning of Kernels for Information Fusion Purposes. CIARP 2008: 277-283 - [c4]Javier González, Alberto Muñoz
Representing Functional Data Using Support Vector Machines. CIARP 2008: 332-339 - 2007
- [c3]Alberto Muñoz, Javier González:
Joint Diagonalization of Kernels for Information Fusion. CIARP 2007: 556-563 - [c2]Javier González, Alberto Muñoz:
Spectral Measures for Kernel Matrices Comparison. ICANN (1) 2007: 727-736 - 2006
- [c1]Alberto Muñoz, Javier González, Isaac Martín de Diego
Local Linear Approximation for Kernel Methods: The Railway Kernel. CIARP 2006: 936-944
Coauthor Index
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