research
∙
06/13/2022
Local distance preserving auto-encoders using Continuous k-Nearest Neighbours graphs
Auto-encoder models that preserve similarities in the data are a popular...
share
research
∙
01/29/2021
Constrained Probabilistic Movement Primitives for Robot Trajectory Adaptation
Versatile movement representations allow robots to learn new tasks and r...
research
∙
08/23/2019
Increasing the Generalisaton Capacity of Conditional VAEs
We address the problem of one-to-many mappings in supervised learning, w...
research
∙
05/13/2019
Learning Hierarchical Priors in VAEs
We propose to learn a hierarchical prior in the context of variational a...
research
∙
06/01/2017
Efficient Low-Order Approximation of First-Passage Time Distributions
We consider the problem of computing first-passage time distributions fo...
research
∙
06/02/2016
f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization
Generative neural samplers are probabilistic models that implement sampl...
research
∙
12/18/2015
Expectation propagation for continuous time stochastic processes
We consider the inverse problem of reconstructing the posterior measure ...
research
∙
01/16/2014
Properties of Bethe Free Energies and Message Passing in Gaussian Models
We address the problem of computing approximate marginals in Gaussian pr...
research
∙
05/17/2013
Factored expectation propagation for input-output FHMM models in systems biology
We consider the problem of joint modelling of metabolic signals and gene...
research
∙
05/17/2013