SafeML: Safety Monitoring of Machine Learning Classifiers through Statistical Difference Measure

27 May 2020

Papers citing "SafeML: Safety Monitoring of Machine Learning Classifiers through Statistical Difference Measure"

8 / 8 papers shown

Title
Fast Predictive Uncertainty for Classification with Bayesian Deep Networks Marius Hobbhahn Agustinus Kristiadi Philipp Hennig BDL UQCV 89 32 0 02 Mar 2020
Secure and Robust Machine Learning for Healthcare: A Survey A. Qayyum Junaid Qadir Muhammad Bilal Ala I. Al-Fuqaha AAML OOD 70 378 0 21 Jan 2020
Calibrated Top-1 Uncertainty estimates for classification by score based models Adam M. Oberman Chris Finlay Alexander Iannantuono Tiago Salvador UQCV 13 3 0 21 Mar 2019
Can You Trust This Prediction? Auditing Pointwise Reliability After Learning Peter F. Schulam Suchi Saria OOD 65 103 0 02 Jan 2019
The Cramer Distance as a Solution to Biased Wasserstein Gradients Marc G. Bellemare Ivo Danihelka Will Dabney S. Mohamed Balaji Lakshminarayanan Stephan Hoyer Rémi Munos GAN 53 344 0 30 May 2017
Improved Training of Wasserstein GANs Ishaan Gulrajani Faruk Ahmed Martín Arjovsky Vincent Dumoulin Aaron Courville GAN 152 9,509 0 31 Mar 2017
Concrete Problems in AI Safety Dario Amodei C. Olah Jacob Steinhardt Paul Christiano John Schulman Dandelion Mané 168 2,371 0 21 Jun 2016
Generative Adversarial Networks Ian Goodfellow Jean Pouget-Abadie M. Berk Mirza Bing Xu David Warde-Farley Sherjil Ozair Aaron Courville Yoshua Bengio GAN 135 2,191 0 10 Jun 2014