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20162020
most citedImperceptible, Robust, and Targeted Adversarial Examples for Automatic Speech Recognition

177 citations · 258 across the 7 of their papers we have counts for

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cs.LG2020

ReZero is All You Need: Fast Convergence at Large Depth

Thomas Bachlechner, Bodhisattwa Prasad Majumder, Huanru Henry Mao +2

Deep networks often suffer from vanishing or exploding gradients due to inefficient signal propagation, leading to long training times or convergence difficulties. Various architec…

cs.LG202015 cited

Deflecting Adversarial Attacks

Yao Qin, Nicholas Frosst, Colin Raffel +2

There has been an ongoing cycle where stronger defenses against adversarial attacks are subsequently broken by a more advanced defense-aware attack. We present a new approach towar…

cs.LG2019

Improving Neural Story Generation by Targeted Common Sense Grounding

Huanru Henry Mao, Bodhisattwa Prasad Majumder, Julian McAuley +1

Stories generated with neural language models have shown promise in grammatical and stylistic consistency. However, the generated stories are still lacking in common sense reasonin…

cs.LG2019

Detecting and Diagnosing Adversarial Images with Class-Conditional Capsule Reconstructions

Yao Qin, Nicholas Frosst, Sara Sabour +3

Adversarial examples raise questions about whether neural network models are sensitive to the same visual features as humans. In this paper, we first detect adversarial examples or…

cs.LG201733 cited

Deep-ESN: A Multiple Projection-encoding Hierarchical Reservoir Computing Framework

Qianli Ma, Lifeng Shen, Garrison W. Cottrell

As an efficient recurrent neural network (RNN) model, reservoir computing (RC) models, such as Echo State Networks, have attracted widespread attention in the last decade. However,…