Yannis Panagakis

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Imperial College London

Lecturer at Middlesex University & Research Fellow at Imperial College London

Polynomial Networks in Deep Classifiers

Deep neural networks have been the driving force behind the success in c...
04/16/2021 ∙ by Grigorios G. Chrysos, et al. ∙ 0 ∙ share

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CoPE: Conditional image generation using Polynomial Expansions

Generative modeling has evolved to a notable field of machine learning. ...
04/11/2021 ∙ by Grigorios G. Chrysos, et al. ∙ 0 ∙ share

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Multilinear Latent Conditioning for Generating Unseen Attribute Combinations

Deep generative models rely on their inductive bias to facilitate genera...
09/09/2020 ∙ by Markos Georgopoulos, et al. ∙ 15 ∙ share

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Deep Polynomial Neural Networks

Deep Convolutional Neural Networks (DCNNs) are currently the method of c...
06/20/2020 ∙ by Grigorios Chrysos, et al. ∙ 66 ∙ share

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Enhancing Facial Data Diversity with Style-based Face Aging

A significant limiting factor in training fair classifiers relates to th...
06/06/2020 ∙ by Markos Georgopoulos, et al. ∙ 3 ∙ share

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Investigating Bias in Deep Face Analysis: The KANFace Dataset and Empirical Study

Deep learning-based methods have pushed the limits of the state-of-the-a...
05/15/2020 ∙ by Markos Georgopoulos, et al. ∙ 14 ∙ share

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Π-nets: Deep Polynomial Neural Networks

Deep Convolutional Neural Networks (DCNNs) is currently the method of ch...
03/08/2020 ∙ by Grigorios G. Chrysos, et al. ∙ 27 ∙ share

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Speech-driven facial animation using polynomial fusion of features

Speech-driven facial animation involves using a speech signal to generat...
12/12/2019 ∙ by Triantafyllos Kefalas, et al. ∙ 15 ∙ share

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PolyGAN: High-Order Polynomial Generators

Generative Adversarial Networks (GANs) have become the gold standard whe...
08/19/2019 ∙ by Grigorios Chrysos, et al. ∙ 9 ∙ share

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Efficient N-Dimensional Convolutions via Higher-Order Factorization

With the unprecedented success of deep convolutional neural networks cam...
06/14/2019 ∙ by Jean Kossaifi, et al. ∙ 3 ∙ share

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Adversarial Learning of Disentangled and Generalizable Representations for Visual Attributes

Recently, a multitude of methods for image-to-image translation has demo...
04/09/2019 ∙ by James Oldfield, et al. ∙ 12 ∙ share

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Stochastically Rank-Regularized Tensor Regression Networks

Over-parametrization of deep neural networks has recently been shown to ...
02/27/2019 ∙ by Arinbjörn Kolbeinsson, et al. ∙ 83 ∙ share

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SEWA DB: A Rich Database for Audio-Visual Emotion and Sentiment Research in the Wild

Natural human-computer interaction and audio-visual human behaviour sens...
01/09/2019 ∙ by Jean Kossaifi, et al. ∙ 8 ∙ share

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Modelling of Facial Aging and Kinship: A Survey

Computational facial models that capture properties of facial cues relat...
02/13/2018 ∙ by Markos Georgopoulos, et al. ∙ 0 ∙ share

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Visual Data Augmentation through Learning

The rapid progress in machine learning methods has been empowered by i) ...
01/20/2018 ∙ by Grigorios G. Chrysos, et al. ∙ 0 ∙ share

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Side Information for Face Completion: a Robust PCA Approach

Robust principal component analysis (RPCA) is a powerful method for lear...
01/20/2018 ∙ by Niannan Xue, et al. ∙ 0 ∙ share

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Robust Kronecker Component Analysis

Dictionary learning and component analysis models are fundamental in lea...
01/18/2018 ∙ by Mehdi Bahri, et al. ∙ 0 ∙ share

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Multi-Attribute Robust Component Analysis for Facial UV Maps

Recently, due to the collection of large scale 3D face models, as well a...
12/15/2017 ∙ by Stylianos Moschoglou, et al. ∙ 0 ∙ share

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GAGAN: Geometry-Aware Generative Adverserial Networks

Deep generative models learned through adversarial training have become ...
12/03/2017 ∙ by Jean Kossaifi, et al. ∙ 0 ∙ share

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An Adversarial Neuro-Tensorial Approach For Learning Disentangled Representations

Several factors contribute to the appearance of an object in a visual sc...
11/28/2017 ∙ by Mengjiao Wang, et al. ∙ 0 ∙ share

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Informed Non-convex Robust Principal Component Analysis with Features

We revisit the problem of robust principal component analysis with featu...
09/14/2017 ∙ by Niannan Xue, et al. ∙ 0 ∙ share

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Robust Kronecker-Decomposable Component Analysis for Low-Rank Modeling

Dictionary learning and component analysis are part of one of the most w...
03/22/2017 ∙ by Mehdi Bahri, et al. ∙ 0 ∙ share

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Side Information in Robust Principal Component Analysis: Algorithms and Applications

Robust Principal Component Analysis (RPCA) aims at recovering a low-rank...
02/02/2017 ∙ by Niannan Xue, et al. ∙ 0 ∙ share

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3D Face Morphable Models "In-the-Wild"

3D Morphable Models (3DMMs) are powerful statistical models of 3D facial...
01/19/2017 ∙ by James Booth, et al. ∙ 0 ∙ share

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Face frontalization for Alignment and Recognition

Recently, it was shown that excellent results can be achieved in both fa...
02/03/2015 ∙ by Christos Sagonas, et al. ∙ 0 ∙ share

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Yannis Panagakis

Featured Co-authors

Anima Anandkumar

Stefanos Zafeiriou

Maja Pantic

Björn Schuller

Jie Shen

Dimitris Samaras

Stavros Petridis

Adrian Bulat

Jing Han

Jiankang Deng

Jean Kossaifi

Polynomial Networks in Deep Classifiers

CoPE: Conditional image generation using Polynomial Expansions

Multilinear Latent Conditioning for Generating Unseen Attribute Combinations

Deep Polynomial Neural Networks

Enhancing Facial Data Diversity with Style-based Face Aging

Investigating Bias in Deep Face Analysis: The KANFace Dataset and Empirical Study

Π-nets: Deep Polynomial Neural Networks

Speech-driven facial animation using polynomial fusion of features

PolyGAN: High-Order Polynomial Generators

Efficient N-Dimensional Convolutions via Higher-Order Factorization

Adversarial Learning of Disentangled and Generalizable Representations for Visual Attributes

Stochastically Rank-Regularized Tensor Regression Networks

SEWA DB: A Rich Database for Audio-Visual Emotion and Sentiment Research in the Wild

Modelling of Facial Aging and Kinship: A Survey

Visual Data Augmentation through Learning

Side Information for Face Completion: a Robust PCA Approach

Robust Kronecker Component Analysis

Multi-Attribute Robust Component Analysis for Facial UV Maps

GAGAN: Geometry-Aware Generative Adverserial Networks

An Adversarial Neuro-Tensorial Approach For Learning Disentangled Representations

Informed Non-convex Robust Principal Component Analysis with Features

Robust Kronecker-Decomposable Component Analysis for Low-Rank Modeling

Side Information in Robust Principal Component Analysis: Algorithms and Applications

3D Face Morphable Models "In-the-Wild"

Face frontalization for Alignment and Recognition