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09/01/2023
Geometry-Informed Neural Operator for Large-Scale 3D PDEs
We propose the geometry-informed neural operator (GINO), a highly effici...
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07/27/2023
Speeding up Fourier Neural Operators via Mixed Precision
The Fourier neural operator (FNO) is a powerful technique for learning s...
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02/14/2023
Score-based Diffusion Models in Function Space
Diffusion models have recently emerged as a powerful framework for gener...
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11/30/2022
HEAT: Hardware-Efficient Automatic Tensor Decomposition for Transformer Compression
Transformers have attained superior performance in natural language proc...
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10/27/2021
Reinforcement Learning in Factored Action Spaces using Tensor Decompositions
We present an extended abstract for the previously published work TESSER...
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10/26/2021
Defensive Tensorization
We propose defensive tensorization, an adversarial defence technique tha...
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10/26/2021
AugMax: Adversarial Composition of Random Augmentations for Robust Training
Data augmentation is a simple yet effective way to improve the robustnes...
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07/07/2021
Tensor Methods in Computer Vision and Deep Learning
Tensors, or multidimensional arrays, are data structures that can natura...
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05/31/2021
Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning
Reinforcement Learning in large action spaces is a challenging problem. ...
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07/17/2020
Unsupervised Controllable Generation with Self-Training
Recent generative adversarial networks (GANs) are able to generate impre...
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04/16/2020
Spectral Learning on Matrices and Tensors
Spectral methods have been the mainstay in several domains such as machi...
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02/25/2020
Toward fast and accurate human pose estimation via soft-gated skip connections
This paper is on highly accurate and highly efficient human pose estimat...
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12/12/2019
Speech-driven facial animation using polynomial fusion of features
Speech-driven facial animation involves using a speech signal to generat...
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06/14/2019
Efficient N-Dimensional Convolutions via Higher-Order Factorization
With the unprecedented success of deep convolutional neural networks cam...
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04/16/2019
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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04/12/2019
Incremental multi-domain learning with network latent tensor factorization
The prominence of deep learning, large amount of annotated data and incr...
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04/11/2019
Improved training of binary networks for human pose estimation and image recognition
Big neural networks trained on large datasets have advanced the state-of...
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04/04/2019
T-Net: Parametrizing Fully Convolutional Nets with a Single High-Order Tensor
Recent findings indicate that over-parametrization, while crucial for su...
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02/27/2019
Stochastically Rank-Regularized Tensor Regression Networks
Over-parametrization of deep neural networks has recently been shown to ...
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01/09/2019
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...
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05/22/2018
Robust Conditional Generative Adversarial Networks
Conditional generative adversarial networks (cGAN) have led to large imp...
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03/05/2018
Stochastic Activation Pruning for Robust Adversarial Defense
Neural networks are known to be vulnerable to adversarial examples. Care...
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12/03/2017
GAGAN: Geometry-Aware Generative Adverserial Networks
Deep generative models learned through adversarial training have become ...
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12/12/2014
