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09/27/2022
Exploring Low Rank Training of Deep Neural Networks
Training deep neural networks in low rank, i.e. with factorised layers, ...
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06/14/2022
Prioritized Training on Points that are Learnable, Worth Learning, and Not Yet Learnt
Training on web-scale data can take months. But most computation and tim...
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07/06/2021
Prioritized training on points that are learnable, worth learning, and not yet learned
We introduce Goldilocks Selection, a technique for faster model training...
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06/04/2021
Self-Attention Between Datapoints: Going Beyond Individual Input-Output Pairs in Deep Learning
We challenge a common assumption underlying most supervised deep learnin...
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03/10/2021
Robustness to Pruning Predicts Generalization in Deep Neural Networks
Existing generalization measures that aim to capture a model's simplicit...
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10/08/2020
Interlocking Backpropagation: Improving depthwise model-parallelism
The number of parameters in state of the art neural networks has drastic...
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07/21/2020
SliceOut: Training Transformers and CNNs faster while using less memory
We demonstrate 10-40 EfficientNets, and Transformer models, with minimal...
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06/08/2020
Wat zei je? Detecting Out-of-Distribution Translations with Variational Transformers
We detect out-of-training-distribution sentences in Neural Machine Trans...
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12/22/2019
A Systematic Comparison of Bayesian Deep Learning Robustness in Diabetic Retinopathy Tasks
Evaluation of Bayesian deep learning (BDL) methods is challenging. We of...
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05/31/2019
Learning Sparse Networks Using Targeted Dropout
Neural networks are easier to optimise when they have many more weights ...
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03/16/2018
Tensor2Tensor for Neural Machine Translation
Tensor2Tensor is a library for deep learning models that is well-suited ...
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01/15/2018
Unsupervised Cipher Cracking Using Discrete GANs
This work details CipherGAN, an architecture inspired by CycleGAN used f...
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07/14/2017
The Reversible Residual Network: Backpropagation Without Storing Activations
Deep residual networks (ResNets) have significantly pushed forward the s...
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06/16/2017
One Model To Learn Them All
Deep learning yields great results across many fields, from speech recog...
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06/12/2017
Attention Is All You Need
The dominant sequence transduction models are based on complex recurrent...
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06/09/2017
