Out of Distribution Data Detection Using Dropout Bayesian Neural Networks

18 February 2022

Papers citing "Out of Distribution Data Detection Using Dropout Bayesian Neural Networks"

7 / 7 papers shown

Title
Logit Disagreement: OoD Detection with Bayesian Neural Networks Kevin Raina UQCV BDL UD PER 66 0 0 24 Feb 2025
On the Privacy Risks of Spiking Neural Networks: A Membership Inference Analysis Junyi Guan Abhijith Sharma Chong Tian Salem Lahlou AAML 49 1 0 18 Feb 2025
Unsupervised Domain Adaptation for Low-dose CT Reconstruction via Bayesian Uncertainty Alignment Kecheng Chen Jie Liu Renjie Wan Victor Ho-Fun Lee Varut Vardhanabhuti Hong Yan Haoliang Li OOD 26 5 0 26 Feb 2023
Probabilistic Embeddings for Cross-Modal Retrieval Sanghyuk Chun Seong Joon Oh Rafael Sampaio de Rezende Yannis Kalantidis Diane Larlus UQCV 412 200 0 13 Jan 2021
Representing smooth functions as compositions of near-identity functions with implications for deep network optimization Peter L. Bartlett S. Evans Philip M. Long 73 31 0 13 Apr 2018
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,138 0 06 Jun 2015
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 266 7,636 0 03 Jul 2012