Victor Gallego
Victor Gallego
Other namesVíctor Gallego Alcalá
Komorebi AI & ICMAT-CSIC
Verified email at - Homepage
Cited by
Cited by
AI in drug development: a multidisciplinary perspective.
V Gallego, R Naveiro, C Roca, D Rios Insua, NE Campillo
Molecular Diversity, 2021
Stochastic Gradient MCMC with Repulsive Forces
V Gallego, DR Insua
NIPS Workshop on Bayesian Deep Learning, 2018
Reinforcement learning under threats
V Gallego, R Naveiro, DR Insua
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 9939-9940, 2019
Adversarial risk analysis: An overview
D Banks, V Gallego, R Naveiro, D Ríos Insua
Wiley Interdisciplinary Reviews: Computational Statistics 14 (1), e1530, 2022
Current advances in neural networks
V Gallego, D Ríos Insua
Annual Review of Statistics and Its Application 9, 197-222, 2022
Opponent Aware Reinforcement Learning
V Gallego, R Naveiro, DR Insua, D Gómez-Ullate
arXiv preprint arXiv:1908.08773, 2019
Assessing the effect of advertising expenditures upon sales: a Bayesian structural time series model
V Gallego, P Angulo, P Suárez-García, D Gómez-Ullate
Applied Stochastic Models in Business and Industry, 1-13, 2019
Waves in isotropic totalistic cellular automata: Application to real-time robot navigation
C Calvo, JA Villacorta-Atienza, VI Mironov, V Gallego, VA Makarov
Advances in Complex Systems 19 (04n05), 1650012, 2016
TUN-AI: Tuna biomass estimation with Machine Learning models trained on oceanography and echosounder FAD data
D Precioso, M Navarro-García, K Gavira-O'Neill, A Torres-Barrán, ...
Fisheries Research 250, 106263, 2022
Adversarial machine learning: Perspectives from adversarial risk analysis
DR Insua, R Naveiro, V Gallego, J Poulos
arXiv preprint arXiv:2003.03546, 2020
Variationally inferred sampling through a refined bound
V Gallego, D Ríos Insua
Entropy 23 (1), 123, 2021
Adversarial machine learning: Bayesian perspectives
D Rios Insua, R Naveiro, V Gallego, J Poulos
Journal of the American Statistical Association 118 (543), 2195-2206, 2023
Personalizing text-to-image generation via aesthetic gradients
V Gallego
NeurIPS 2022, Workshop on Machine Learning for Creativity and Design, 2022
Perspectives on adversarial classification
D Rios Insua, R Naveiro, V Gallego
Mathematics 8 (11), 1957, 2020
Protecting classifiers from attacks. a bayesian approach
V Gallego, R Naveiro, A Redondo, DR Insua, F Ruggeri
arXiv preprint arXiv:2004.08705, 2020
Synchronization of heteroclinic circuits through learning in chains of neural motifs
VA Makarov, C Calvo, V Gallego, A Selskii
IFAC-PapersOnLine 49 (14), 80-83, 2016
Learning connectivity structure in a chain of network motifs
C Calvo, V Gallego, A Selskii, VA Makarov
Advanced Science Letters 22 (10), 2647-2651, 2016
Zyn: Zero-shot reward models with yes-no questions
V Gallego
arXiv preprint arXiv:2308.06385, 2023
Bayesian Factorization Machines for Risk Management and Robust Decision Making
P Angulo, V Gallego, D Gómez-Ullate, P Suárez-García
Mathematical and Statistical Methods for Actuarial Sciences and Finance: MAF …, 2018
Distilled self-critique of llms with synthetic data: a bayesian perspective
V Gallego
arXiv preprint arXiv:2312.01957, 2023
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