Topological Uncertainty: Monitoring trained neural networks through persistence of activation graphs

7 May 2021

Papers citing "Topological Uncertainty: Monitoring trained neural networks through persistence of activation graphs"

9 / 9 papers shown

Title
Topology of Out-of-Distribution Examples in Deep Neural Networks Esha Datta Johanna Hennig Eva Domschot Connor Mattes Michael R. Smith 72 0 0 21 Jan 2025
Addressing caveats of neural persistence with deep graph persistence Leander Girrbach Anders Christensen Ole Winther Zeynep Akata A. Sophia Koepke GNN 20 1 0 20 Jul 2023
Experimental Observations of the Topology of Convolutional Neural Network Activations Emilie Purvine Davis Brown Brett Jefferson C. Joslyn Brenda Praggastis Archit Rathore Madelyn Shapiro Bei Wang Youjia Zhou AI4CE 40 12 0 01 Dec 2022
Zeroth-Order Topological Insights into Iterative Magnitude Pruning Aishwarya H. Balwani J. Krzyston 29 2 0 14 Jun 2022
Trustworthy Graph Neural Networks: Aspects, Methods and Trends He Zhang Bang Wu Xingliang Yuan Shirui Pan Hanghang Tong Jian Pei 45 104 0 16 May 2022
Persformer: A Transformer Architecture for Topological Machine Learning Raphael Reinauer Matteo Caorsi Nicolas Berkouk 29 15 0 30 Dec 2021
Nonparametric Topological Layers in Neural Networks Dongfang Zhao 13 0 0 27 Nov 2021
Topological Detection of Trojaned Neural Networks Songzhu Zheng Yikai Zhang H. Wagner Mayank Goswami Chao Chen AAML 26 40 0 11 Jun 2021
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,661 0 05 Dec 2016