32 citations · 41 across the 8 of their papers we have counts for
10 papers
Dimensionality Reduction as Probabilistic Inference
Aditya Ravuri, Francisco Vargas, Vidhi Lalchand +1
Dimensionality reduction (DR) algorithms compress high-dimensional data into a lower dimensional representation while preserving important features of the data. DR is a critical st…
To smooth a cloud or to pin it down: Guarantees and Insights on Score Matching in Denoising Diffusion Models
Francisco Vargas, Teodora Reu, Anna Kerekes +1
Denoising diffusion models are a class of generative models which have recently achieved state-of-the-art results across many domains. Gradual noise is added to the data using a di…
Denoising Diffusion Samplers
Francisco Vargas, Will Grathwohl, Arnaud Doucet
Denoising diffusion models are a popular class of generative models providing state-of-the-art results in many domains. One adds gradually noise to data using a diffusion to transf…
Kernelized Concept Erasure
Shauli Ravfogel, Francisco Vargas, Yoav Goldberg +1
The representation space of neural models for textual data emerges in an unsupervised manner during training. Understanding how those representations encode human-interpretable con…
Bayesian Learning via Neural Schrödinger-Föllmer Flows
Francisco Vargas, Andrius Ovsianas, David Fernandes +3
In this work we explore a new framework for approximate Bayesian inference in large datasets based on stochastic control (i.e. Schrödinger bridges). We advocate stochastic control…
Efficient privacy-preserving inference for convolutional neural networks
Han Xuanyuan, Francisco Vargas, Stephen Cummins
The processing of sensitive user data using deep learning models is an area that has gained recent traction. Existing work has leveraged homomorphic encryption (HE) schemes to enab…
Solving Schrödinger Bridges via Maximum Likelihood
Francisco Vargas, Pierre Thodoroff, Neil D. Lawrence +1
The Schrödinger bridge problem (SBP) finds the most likely stochastic evolution between two probability distributions given a prior stochastic evolution. As well as applications in…
Exploring the Linear Subspace Hypothesis in Gender Bias Mitigation
Francisco Vargas, Ryan Cotterell
Bolukbasi et al. (2016) presents one of the first gender bias mitigation techniques for word representations. Their method takes pre-trained word representations as input and attem…
Multilingual Factor Analysis
Francisco Vargas, Kamen Brestnichki, Alex Papadopoulos-Korfiatis +1
In this work we approach the task of learning multilingual word representations in an offline manner by fitting a generative latent variable model to a multilingual dictionary. We…
Model Comparison for Semantic Grouping
Francisco Vargas, Kamen Brestnichki, Nils Hammerla
We introduce a probabilistic framework for quantifying the semantic similarity between two groups of embeddings. We formulate the task of semantic similarity as a model comparison…