
Tensor Methods in Computer Vision and Deep Learning
Tensors, or multidimensional arrays, are data structures that can natura...
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Tesseract: Tensorised Actors for MultiAgent Reinforcement Learning
Reinforcement Learning in large action spaces is a challenging problem. ...
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Unsupervised Controllable Generation with SelfTraining
Recent generative adversarial networks (GANs) are able to generate impre...
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Spectral Learning on Matrices and Tensors
Spectral methods have been the mainstay in several domains such as machi...
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Toward fast and accurate human pose estimation via softgated skip connections
This paper is on highly accurate and highly efficient human pose estimat...
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Speechdriven facial animation using polynomial fusion of features
Speechdriven facial animation involves using a speech signal to generat...
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Efficient NDimensional Convolutions via HigherOrder Factorization
With the unprecedented success of deep convolutional neural networks cam...
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Matrix and tensor decompositions for training binary neural networks
This paper is on improving the training of binary neural networks in whi...
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Incremental multidomain learning with network latent tensor factorization
The prominence of deep learning, large amount of annotated data and incr...
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Improved training of binary networks for human pose estimation and image recognition
Big neural networks trained on large datasets have advanced the stateof...
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TNet: Parametrizing Fully Convolutional Nets with a Single HighOrder Tensor
Recent findings indicate that overparametrization, while crucial for su...
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Stochastically RankRegularized Tensor Regression Networks
Overparametrization of deep neural networks has recently been shown to ...
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SEWA DB: A Rich Database for AudioVisual Emotion and Sentiment Research in the Wild
Natural humancomputer interaction and audiovisual human behaviour sens...
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Robust Conditional Generative Adversarial Networks
Conditional generative adversarial networks (cGAN) have led to large imp...
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Stochastic Activation Pruning for Robust Adversarial Defense
Neural networks are known to be vulnerable to adversarial examples. Care...
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GAGAN: GeometryAware Generative Adverserial Networks
Deep generative models learned through adversarial training have become ...
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Machine Learning for Neuroimaging with ScikitLearn
Statistical machine learning methods are increasingly used for neuroimag...
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Jean Kossaifi
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