204 citations · 306 across the 21 of their papers we have counts for
6 papers · 1 filter
Nudge Attacks on Point-Cloud DNNs
Yiren Zhao, Ilia Shumailov, Robert Mullins +1
The wide adaption of 3D point-cloud data in safety-critical applications such as autonomous driving makes adversarial samples a real threat. Existing adversarial attacks on point c…
Learned Low Precision Graph Neural Networks
Yiren Zhao, Duo Wang, Daniel Bates +3
Deep Graph Neural Networks (GNNs) show promising performance on a range of graph tasks, yet at present are costly to run and lack many of the optimisations applied to DNNs. We show…
Sponge Examples: Energy-Latency Attacks on Neural Networks
Ilia Shumailov, Yiren Zhao, Daniel Bates +3
The high energy costs of neural network training and inference led to the use of acceleration hardware such as GPUs and TPUs. While this enabled us to train large-scale neural netw…
Accelerate Cycle-Level Full-System Simulation of Multi-Core RISC-V Systems with Binary Translation
Xuan Guo, Robert Mullins
It has always been difficult to balance the accuracy and performance of ISSs. RTL simulators or systems such as gem5 are used to execute programs in a cycle-accurate manner but are…
Probabilistic Dual Network Architecture Search on Graphs
Yiren Zhao, Duo Wang, Xitong Gao +3
We present the first differentiable Network Architecture Search (NAS) for Graph Neural Networks (GNNs). GNNs show promising performance on a wide range of tasks, but require a larg…
Towards Certifiable Adversarial Sample Detection
Ilia Shumailov, Yiren Zhao, Robert Mullins +1
Convolutional Neural Networks (CNNs) are deployed in more and more classification systems, but adversarial samples can be maliciously crafted to trick them, and are becoming a real…