3 citations · 5 across the 6 of their papers we have counts for
6 papers
Two behavioural pseudometrics for continuous-time Markov processes
Linan Chen, Florence Clerc, Prakash Panangaden
Bisimulation is a concept that captures behavioural equivalence of states in a variety of types of transition systems. It has been widely studied in discrete-time settings where a…
A behavioural pseudometric for continuous-time Markov processes
Linan Chen, Florence Clerc, Prakash Panangaden
In this work, we generalize the concept of bisimulation metric in order to metrize the behaviour of continuous-time processes. Similarly to what is done for discrete-time systems,…
Behavioural pseudometrics for continuous-time diffusions
Linan Chen, Florence Clerc, Prakash Panangaden
Bisimulation is a concept that captures behavioural equivalence of states in a variety of types of transition systems. It has been widely studied in a discrete-time setting where t…
Statistical Guarantees for Variational Autoencoders using PAC-Bayesian Theory
Sokhna Diarra Mbacke, Florence Clerc, Pascal Germain
Since their inception, Variational Autoencoders (VAEs) have become central in machine learning. Despite their widespread use, numerous questions regarding their theoretical propert…
PAC-Bayesian Generalization Bounds for Adversarial Generative Models
Sokhna Diarra Mbacke, Florence Clerc, Pascal Germain
We extend PAC-Bayesian theory to generative models and develop generalization bounds for models based on the Wasserstein distance and the total variation distance. Our first result…
Bisimulation for Feller-Dynkin Processes
Linan Chen, Florence Clerc, Prakash Panangaden
Bisimulation is a concept that captures behavioural equivalence. It has been studied extensively on nonprobabilistic systems and on discrete-time Markov processes and on so-called…