Insights into Fairness through Trust: Multi-scale Trust Quantification for Financial Deep Learning

3 November 2020

Papers citing "Insights into Fairness through Trust: Multi-scale Trust Quantification for Financial Deep Learning"

8 / 8 papers shown

Title
Where Does Trust Break Down? A Quantitative Trust Analysis of Deep Neural Networks via Trust Matrix and Conditional Trust Densities Andrew Hryniowski Xiao Yu Wang A. Wong 63 10 0 30 Sep 2020
How Much Can We Really Trust You? Towards Simple, Interpretable Trust Quantification Metrics for Deep Neural Networks A. Wong Xiao Yu Wang Andrew Hryniowski 56 23 0 12 Sep 2020
Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics Mark Weber Giacomo Domeniconi Jie Chen D. Weidele Claudio Bellei Tom Robinson C. E. Leiserson 76 327 0 31 Jul 2019
Trading via Image Classification N. Cohen T. Balch Manuela Veloso 75 34 0 23 Jul 2019
To Trust Or Not To Trust A Classifier Heinrich Jiang Been Kim Melody Y. Guan Maya R. Gupta UQCV 182 473 0 30 May 2018
Listening to Chaotic Whispers: A Deep Learning Framework for News-oriented Stock Trend Prediction Ziniu Hu Weiqing Liu Jiang Bian Xuanzhe Liu Tie-Yan Liu 51 308 0 06 Dec 2017
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? Alex Kendall Y. Gal BDL OOD UD UQCV PER 377 4,724 0 15 Mar 2017
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 903 9,364 0 06 Jun 2015