-
Mind the Gap when Conditioning Amortised Inference in Sequential Latent-Variable Models
Amortised inference enables scalable learning of sequential latent-varia...
01/18/2021 ∙ by Justin Bayer, et al. ∙
0
∙
share
read it
-
Variational State-Space Models for Localisation and Dense 3D Mapping in 6 DoF
We solve the problem of 6-DoF localisation and 3D dense reconstruction i...
06/17/2020 ∙ by Atanas Mirchev, et al. ∙
8
∙
share
read it
-
Approximate Bayesian inference in spatial environments
We propose to learn a stochastic recurrent model to solve the problem of...
05/18/2018 ∙ by Atanas Mirchev, et al. ∙
0
∙
share
read it
-
Classification of sparsely labeled spatio-temporal data through semi-supervised adversarial learning
In recent years, Generative Adversarial Networks (GAN) have emerged as a...
01/26/2018 ∙ by Atanas Mirchev, et al. ∙
0
∙
share
read it
-
3D Deep Learning for Biological Function Prediction from Physical Fields
Predicting the biological function of molecules, be it proteins or drug-...
04/13/2017 ∙ by Vladimir Golkov, et al. ∙
0
∙
share
read it
