297 citations · 327 across the 8 of their papers we have counts for
9 papers
Spoken Language Understanding on the Edge
Alaa Saade, Alice Coucke, Alexandre Caulier +9
We consider the problem of performing Spoken Language Understanding (SLU) on small devices typical of IoT applications. Our contributions are twofold. First, we outline the design…
Federated Learning for Keyword Spotting
David Leroy, Alice Coucke, Thibaut Lavril +2
We propose a practical approach based on federated learning to solve out-of-domain issues with continuously running embedded speech-based models such as wake word detectors. We con…
Snips Voice Platform: an embedded Spoken Language Understanding system for private-by-design voice interfaces
Alice Coucke, Alaa Saade, Adrien Ball +9
This paper presents the machine learning architecture of the Snips Voice Platform, a software solution to perform Spoken Language Understanding on microprocessors typical of IoT de…
Learning Operations on a Stack with Neural Turing Machines
Tristan Deleu, Joseph Dureau
Multiple extensions of Recurrent Neural Networks (RNNs) have been proposed recently to address the difficulty of storing information over long time periods. In this paper, we exper…
SSM: Inference for time series analysis with State Space Models
Joseph Dureau, Sébastien Ballesteros, Tiffany Bogich
The main motivation behind the open source library SSM is to reduce the technical friction that prevents modellers from sharing their work, quickly iterating in crisis situations,…
Bayesian Inference for partially observed SDEs Driven by Fractional Brownian Motion
Alexandros Beskos, Joseph Dureau, Konstantinos Kalogeropoulos
We consider continuous-time diffusion models driven by fractional Brownian motion. Observations are assumed to possess a non-trivial likelihood given the latent path. Due to the no…
Quick overview of inference methods in PLoM: combining fast and exact plug-and-play algorithms to achieve flexibility, precision and efficiency
Antoine Basset, Joseph Dureau, Sébastien Ballesteros +1
Overview of inference methods in PLoM.
A Bayesian approach to estimate changes in condom use from limited HIV prevalence data
Joseph Dureau, Konstantinos Kalogeropoulos, Peter Vickerman +2
Evaluation of HIV large scale interventions programme is becoming increasingly important, but impact estimates frequently hinge on knowledge of changes in behaviour such as the fre…
Capturing the time-varying drivers of an epidemic using stochastic dynamical systems
Joseph Dureau, Konstantinos Kalogeropoulos, Marc Baguelin
Epidemics are often modelled using non-linear dynamical systems observed through partial and noisy data. In this paper, we consider stochastic extensions in order to capture unknow…