Javier Gonzalez
26 papers · 2016–2026 · 8 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (7) π Academic Marathon (9) π Interdisciplinary Bridge π§ Keyword Pioneer π Cross-Pollinator (13)
π
Conference Polyglot
(7)
π£
Hot Topic Early Bird
π
Academic Marathon
(9)
π¬
Deep Specialist
(12)
π₯
Unstoppable
(7)
β‘
Prolific Year
(5)
π
Conference Pioneer
π
Century Club
(25)
β
The Questioner
π
Trend Setter
ποΈ
Keyword Collector
(80)
Conferences
ICML (7)
NIPS (7)
AISTATS (6)
CLEAR (2)
EACL (1)
ICLR (1)
JMLR (1)
UAI (1)
Top co-authors
Keywords
bayesian optimization
(11)
gaussian process
(8)
causal inference
(4)
acquisition function
(3)
multi-task learning
(2)
kernel mean embedding
(2)
causal bayesian optimization
(2)
active learning
(2)
batch optimization
(2)
preference learning
(2)
uncertainty quantification
(2)
large language model
(2)
hyperparameter optimization
(2)
bayesian quadrature
(2)
surrogate model
(2)
reproducing kernel hilbert space
(2)
global optimization
(1)
sentiment analysis
(1)
feature attribution
(1)
cultural nuance
(1)
Papers
Reasoning Beyond Labels: Measuring LLM Sentiment in Low-Resource, Culturally Nuanced Contexts
EACL 2026
Beyond Flatland: A Geometric Take on Matching Methods for Treatment Effect Estimation
CLEAR 2025
RE-IMAGINE: Symbolic Benchmark Synthesis for Reasoning Evaluation
ICML 2025
Compositional Causal Reasoning Evaluation in Language Models
ICML 2025
Reasoning Elicitation in Language Models via Counterfactual Feedback
ICLR 2025
Cautionary Tales on Synthetic Controls in Survival Analyses
CLEAR 2024
Does Reasoning Emerge? Examining the Probabilities of Causation in Large Language Models
NIPS 2024
Safe Exploration in Dose Finding Clinical Trials with Heterogeneous Participants
ICML 2024
RKHS-SHAP: Shapley Values for Kernel Methods
NIPS 2022
Predicting the impact of treatments over time with uncertainty aware neural differential equations.
AISTATS 2022
Learning Inconsistent Preferences with Gaussian Processes
AISTATS 2022
Dynamic Causal Bayesian Optimization
NIPS 2021
GIBBON: General-purpose Information-Based Bayesian Optimisation
JMLR 2021
BayesIMP: Uncertainty Quantification for Causal Data Fusion
NIPS 2021
Bandit optimisation of functions in the MatΓ©rn kernel RKHS
AISTATS 2020
Multi-task Causal Learning with Gaussian Processes
NIPS 2020
Causal Bayesian Optimization
AISTATS 2020
BINOCULARS for efficient, nonmyopic sequential experimental design
ICML 2020
BOSS: Bayesian Optimization over String Spaces
NIPS 2020
Active Multi-Information Source Bayesian Quadrature
UAI 2019
Meta-Surrogate Benchmarking for Hyperparameter Optimization
NIPS 2019
Structured Variationally Auto-encoded Optimization
ICML 2018
Bayesian Optimization with Tree-structured Dependencies
ICML 2017
Preferential Bayesian Optimization
ICML 2017
Batch Bayesian Optimization via Local Penalization
AISTATS 2016
GLASSES: Relieving The Myopia Of Bayesian Optimisation
AISTATS 2016