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Mind the Gap when Conditioning Amortised Inference in Sequential Latent-Variable Models
Amortised inference enables scalable learning of sequential latent-varia...
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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...
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Approximate Bayesian inference in spatial environments
We propose to learn a stochastic recurrent model to solve the problem of...
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Classification of sparsely labeled spatio-temporal data through semi-supervised adversarial learning
In recent years, Generative Adversarial Networks (GAN) have emerged as a...
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3D Deep Learning for Biological Function Prediction from Physical Fields
Predicting the biological function of molecules, be it proteins or drug-...
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Atanas Mirchev
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