Search Results for author: Stefanos Eleftheriadis

Found 9 papers, 0 papers with code

Sparse Gaussian Processes with Spherical Harmonic Features Revisited

no code implementations28 Mar 2023 Stefanos Eleftheriadis, Dominic Richards, James Hensman

Further, we introduce sparseness in the eigenbasis by variational learning of the spherical harmonic phases.

Gaussian Processes

Doubly Sparse Variational Gaussian Processes

no code implementations15 Jan 2020 Vincent Adam, Stefanos Eleftheriadis, Nicolas Durrande, Artem Artemev, James Hensman

The use of Gaussian process models is typically limited to datasets with a few tens of thousands of observations due to their complexity and memory footprint.

Gaussian Processes valid

Banded Matrix Operators for Gaussian Markov Models in the Automatic Differentiation Era

no code implementations26 Feb 2019 Nicolas Durrande, Vincent Adam, Lucas Bordeaux, Stefanos Eleftheriadis, James Hensman

Banded matrices can be used as precision matrices in several models including linear state-space models, some Gaussian processes, and Gaussian Markov random fields.

Gaussian Processes Variational Inference

Natural Gradients in Practice: Non-Conjugate Variational Inference in Gaussian Process Models

no code implementations24 Mar 2018 Hugh Salimbeni, Stefanos Eleftheriadis, James Hensman

The natural gradient method has been used effectively in conjugate Gaussian process models, but the non-conjugate case has been largely unexplored.

Variational Inference

Identification of Gaussian Process State Space Models

no code implementations NeurIPS 2017 Stefanos Eleftheriadis, Thomas F. W. Nicholson, Marc Peter Deisenroth, James Hensman

To address this challenge, we impose a structured Gaussian variational posterior distribution over the latent states, which is parameterised by a recognition model in the form of a bi-directional recurrent neural network.

Variational Gaussian Process Auto-Encoder for Ordinal Prediction of Facial Action Units

no code implementations16 Aug 2016 Stefanos Eleftheriadis, Ognjen Rudovic, Marc P. Deisenroth, Maja Pantic

In particular, we introduce GP encoders to project multiple observed features onto a latent space, while GP decoders are responsible for reconstructing the original features.

Gaussian Process Domain Experts for Model Adaptation in Facial Behavior Analysis

no code implementations11 Apr 2016 Stefanos Eleftheriadis, Ognjen Rudovic, Marc P. Deisenroth, Maja Pantic

The adaptation of the classifier is facilitated in probabilistic fashion by conditioning the target expert on multiple source experts.

Domain Adaptation Gaussian Processes +1

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