32 citations · 41 across the 8 of their papers we have counts for
3 papers · 1 filter
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…