Focused Quantization for Sparse CNNs

1 code implementation • NeurIPS 2019 • Yiren Zhao, Xitong Gao, Daniel Bates, Robert Mullins, Cheng-Zhong Xu

In ResNet-50, we achieved a 18. 08x CR with only 0. 24% loss in top-5 accuracy, outperforming existing compression methods.

Neural Network Compression Quantization

Sponge Examples: Energy-Latency Attacks on Neural Networks

2 code implementations • 5 Jun 2020 • Ilia Shumailov, Yiren Zhao, Daniel Bates, Nicolas Papernot, Robert Mullins, Ross Anderson

The high energy costs of neural network training and inference led to the use of acceleration hardware such as GPUs and TPUs.

Autonomous Vehicles

Learned Low Precision Graph Neural Networks

no code implementations • 19 Sep 2020 • Yiren Zhao, Duo Wang, Daniel Bates, Robert Mullins, Mateja Jamnik, Pietro Lio

LPGNAS learns the optimal architecture coupled with the best quantisation strategy for different components in the GNN automatically using back-propagation in a single search round.

Fast Neural Network based Solving of Partial Differential Equations

no code implementations • 18 May 2022 • Jaroslaw Rzepecki, Daniel Bates, Chris Doran

We present a novel method for using Neural Networks (NNs) for finding solutions to a class of Partial Differential Equations (PDEs).