Into the Unknown: Active Monitoring of Neural Networks

14 September 2020

Papers citing "Into the Unknown: Active Monitoring of Neural Networks"

9 / 9 papers shown

Title
Online Safety Analysis for LLMs: a Benchmark, an Assessment, and a Path Forward Xuan Xie Jiayang Song Zhehua Zhou Yuheng Huang Da Song Lei Ma OffRL 53 6 0 12 Apr 2024
What, Indeed, is an Achievable Provable Guarantee for Learning-Enabled Safety Critical Systems Saddek Bensalem Chih-Hong Cheng Wei Huang Xiaowei Huang Changshun Wu Xingyu Zhao AAML 29 6 0 20 Jul 2023
Conformal Prediction for STL Runtime Verification Lars Lindemann Xin Qin Jyotirmoy V. Deshmukh George J. Pappas 32 45 0 03 Nov 2022
Unifying Evaluation of Machine Learning Safety Monitors Joris Guérin Raul Sena Ferreira Kevin Delmas Jérémie Guiochet 35 12 0 31 Aug 2022
Verification-Aided Deep Ensemble Selection Guy Amir Tom Zelazny Guy Katz Michael Schapira AAML 30 18 0 08 Feb 2022
An Abstraction-Refinement Approach to Verifying Convolutional Neural Networks Matan Ostrovsky Clark W. Barrett Guy Katz 40 26 0 06 Jan 2022
Run-Time Monitoring of Machine Learning for Robotic Perception: A Survey of Emerging Trends Q. Rahman Peter Corke Feras Dayoub OOD 42 51 0 05 Jan 2021
Provably-Robust Runtime Monitoring of Neuron Activation Patterns Chih-Hong Cheng AAML 40 12 0 24 Nov 2020
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 287 9,156 0 06 Jun 2015