no code implementations • 7 Feb 2023 • Xiu-Shen Wei, Xuhao Sun, Yang shen, Anqi Xu, Peng Wang, Faen Zhang
Simplicity Bias (SB) is a phenomenon that deep neural networks tend to rely favorably on simpler predictive patterns but ignore some complex features when applied to supervised discriminative tasks.
Ranked #4 on Long-tail Learning on CIFAR-10-LT (ρ=10)
1 code implementation • 20 Apr 2022 • Daniel R. van Niekerk, Anqi Xu, Branislav Gerazov, Paul K. Krug, Peter Birkholz, Yi Xu
High-quality articulatory speech synthesis has many potential applications in speech science and technology.
no code implementations • 16 Oct 2021 • Rey Reza Wiyatno, Anqi Xu, Liam Paull
Commonly, learning-based topological navigation approaches produce a local policy while preserving some loose connectivity of the space through a topological map.
no code implementations • 20 May 2020 • Branislav Gerazov, Daniel van Niekerk, Anqi Xu, Paul Konstantin Krug, Peter Birkholz, Yi Xu
One of the crucial parameters in these simulations is the choice of features and a metric to evaluate the acoustic error between the synthesised sound and the reference target.
1 code implementation • 13 Nov 2019 • Rey Reza Wiyatno, Anqi Xu, Ousmane Dia, Archy de Berker
Recent research has found that many families of machine learning models are vulnerable to adversarial examples: inputs that are specifically designed to cause the target model to produce erroneous outputs.
no code implementations • ICCV 2019 • Rey Reza Wiyatno, Anqi Xu
We present a system for generating inconspicuous-looking textures that, when displayed in the physical world as digital or printed posters, cause visual object tracking systems to become confused.
no code implementations • 15 Dec 2018 • Joel Lamy-Poirier, Anqi Xu
We present Hinted Networks: a collection of architectural transformations for improving the accuracies of neural network models for regression tasks, through the injection of a prior for the output prediction (i. e. a hint).
no code implementations • 23 Aug 2018 • Rey Wiyatno, Anqi Xu
The Jacobian-based Saliency Map Attack is a family of adversarial attack methods for fooling classification models, such as deep neural networks for image classification tasks.
1 code implementation • 25 Sep 2017 • Florian Shkurti, Wei-Di Chang, Peter Henderson, Md Jahidul Islam, Juan Camilo Gamboa Higuera, Jimmy Li, Travis Manderson, Anqi Xu, Gregory Dudek, Junaed Sattar
We present a robust multi-robot convoying approach that relies on visual detection of the leading agent, thus enabling target following in unstructured 3-D environments.