6 citations · 6 across the 4 of their papers we have counts for
7 papers
Personalizing Text-to-Image Generation via Aesthetic Gradients
Victor Gallego
This work proposes aesthetic gradients, a method to personalize a CLIP-conditioned diffusion model by guiding the generative process towards custom aesthetics defined by the user f…
Contributions to Large Scale Bayesian Inference and Adversarial Machine Learning
Víctor Gallego
The rampant adoption of ML methodologies has revealed that models are usually adopted to make decisions without taking into account the uncertainties in their predictions. More cri…
Data sharing games
Víctor Gallego, Roi Naveiro, David Ríos Insua +1
Data sharing issues pervade online social and economic environments. To foster social progress, it is important to develop models of the interaction between data producers and cons…
Adversarial Risk Analysis (Overview)
David Banks, Víctor Gallego, Roi Naveiro +1
Adversarial risk analysis (ARA) is a relatively new area of research that informs decision-making when facing intelligent opponents and uncertain outcomes. It enables an analyst to…
Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs
Victor Gallego, David Rios Insua
A framework to boost the efficiency of Bayesian inference in probabilistic programs is introduced by embedding a sampler inside a variational posterior approximation. We call it th…
Stochastic Gradient MCMC with Repulsive Forces
Victor Gallego, David Rios Insua
We propose a unifying view of two different Bayesian inference algorithms, Stochastic Gradient Markov Chain Monte Carlo (SG-MCMC) and Stein Variational Gradient Descent (SVGD), lea…