Classification Uncertainty of Deep Neural Networks Based on Gradient Information

22 May 2018

Papers citing "Classification Uncertainty of Deep Neural Networks Based on Gradient Information"

48 / 48 papers shown

Title
ATM-Net: Anatomy-Aware Text-Guided Multi-Modal Fusion for Fine-Grained Lumbar Spine Segmentation Sheng Lian Dengfeng Pan Jianlong Cai Guang-Yong Chen Zhun Zhong Zhiming Luo Shen Zhao Shuo Li 36 0 0 04 Apr 2025
Revisiting Gradient-based Uncertainty for Monocular Depth Estimation Julia Hornauer Amir El-Ghoussani Vasileios Belagiannis UQCV 61 0 0 09 Feb 2025
Context-Based Echo State Networks with Prediction Confidence for Human-Robot Shared Control Negin Amirshirzad Mehmet Arda Eren Erhan Oztop 67 0 0 30 Nov 2024
A Comprehensive Survey on Evidential Deep Learning and Its Applications Junyu Gao Mengyuan Chen Liangyu Xiang Changsheng Xu EDL BDL UQCV 62 5 0 07 Sep 2024
Understanding the Dependence of Perception Model Competency on Regions in an Image Sara Pohland Claire Tomlin 19 1 0 15 Jul 2024
A Structured Review of Literature on Uncertainty in Machine Learning & Deep Learning Fahimeh Fakour Ali Mosleh Ramin Ramezani UQCV UD PER 51 3 0 01 Jun 2024
LUQ: Long-text Uncertainty Quantification for LLMs Caiqi Zhang Fangyu Liu Marco Basaldella Nigel Collier HILM 58 25 0 29 Mar 2024
Uncertainty Driven Active Learning for Image Segmentation in Underwater Inspection Luiza Ribeiro Marnet Yury Brodskiy Stella Grasshof Andrzej Wasowski 32 2 0 20 Mar 2024
Uncertainty Quantification using Generative Approach Yunsheng Zhang UQCV BDL 19 0 0 13 Oct 2023
Uncertainty quantification for deep learning-based schemes for solving high-dimensional backward stochastic differential equations Lorenc Kapllani Long Teng Matthias Rottmann 27 1 0 05 Oct 2023
Out-of-Distribution Detection by Leveraging Between-Layer Transformation Smoothness Fran Jelenić Josip Jukić Martin Tutek Mate Puljiz Jan vSnajder OODD 34 5 0 04 Oct 2023
Look Before You Leap: An Exploratory Study of Uncertainty Measurement for Large Language Models Yuheng Huang Jiayang Song Zhijie Wang Shengming Zhao Huaming Chen Felix Juefei-Xu Lei Ma 33 34 0 16 Jul 2023
GIT: Detecting Uncertainty, Out-Of-Distribution and Adversarial Samples using Gradients and Invariance Transformations Julia Lust Alexandru Paul Condurache AAML UQCV 29 0 0 05 Jul 2023
Single-model uncertainty quantification in neural network potentials does not consistently outperform model ensembles Aik Rui Tan S. Urata Samuel Goldman Johannes C. B. Dietschreit Rafael Gómez-Bombarelli BDL 43 42 0 02 May 2023
Compensation Learning in Semantic Segmentation Timo Kaiser Christoph Reinders Bodo Rosenhahn NoLa 42 3 0 26 Apr 2023
Probing the Purview of Neural Networks via Gradient Analysis Jinsol Lee Charles Lehman Mohit Prabhushankar Ghassan AlRegib 34 7 0 06 Apr 2023
Delay-SDE-net: A deep learning approach for time series modelling with memory and uncertainty estimates M. Eggen A. Midtfjord 29 2 0 14 Mar 2023
Pixel-wise Gradient Uncertainty for Convolutional Neural Networks applied to Out-of-Distribution Segmentation Kira Maag Tobias Riedlinger UQCV 38 7 0 13 Mar 2023
Learning Complementary Policies for Human-AI Teams Ruijiang Gao M. Saar-Tsechansky Maria De-Arteaga Ligong Han Wei-Ju Sun Min Kyung Lee Matthew Lease 38 8 0 06 Feb 2023
Generalized Uncertainty of Deep Neural Networks: Taxonomy and Applications Chengyu Dong OOD UQCV BDL AI4CE 44 0 0 02 Feb 2023
Gradient-based Uncertainty for Monocular Depth Estimation Julia Hornauer Vasileios Belagiannis UQCV 32 32 0 03 Aug 2022
Gradient-Based Adversarial and Out-of-Distribution Detection Jinsol Lee Mohit Prabhushankar Ghassan AlRegib UQCV 40 13 0 16 Jun 2022
Open-Set Recognition with Gradient-Based Representations Jinsol Lee Ghassan AlRegib VLM BDL 19 9 0 16 Jun 2022
WOOD: Wasserstein-based Out-of-Distribution Detection Yinan Wang Wenbo Sun Jionghua Jin Zhen Kong Xiaowei Yue OODD 20 8 0 13 Dec 2021
Benchmark for Out-of-Distribution Detection in Deep Reinforcement Learning Aaqib Parvez Mohammed Matias Valdenegro-Toro OOD OffRL 24 10 0 05 Dec 2021
Exploring the Limits of Epistemic Uncertainty Quantification in Low-Shot Settings Matias Valdenegro-Toro UQCV 25 2 0 18 Nov 2021
Latent Cognizance: What Machine Really Learns Pisit Nakjai J. Ponsawat Tatpong Katanyukul BDL 18 3 0 29 Oct 2021
Recognition Awareness: An Application of Latent Cognizance to Open-Set Recognition Tatpong Katanyukul Pisit Nakjai BDL 27 1 0 27 Aug 2021
Resisting Out-of-Distribution Data Problem in Perturbation of XAI Luyu Qiu Yi Yang Caleb Chen Cao Jing Liu Yueyuan Zheng H. Ngai J. H. Hsiao Lei Chen 19 18 0 27 Jul 2021
Improving Variational Autoencoder based Out-of-Distribution Detection for Embedded Real-time Applications Yeli Feng Daniel Jun Xian Ng Arvind Easwaran OODD 38 17 0 25 Jul 2021
Gradient-Based Quantification of Epistemic Uncertainty for Deep Object Detectors Tobias Riedlinger Matthias Rottmann Marius Schubert Hanno Gottschalk BDL UQCV 14 12 0 09 Jul 2021
A Survey of Uncertainty in Deep Neural Networks J. Gawlikowski Cedrique Rovile Njieutcheu Tassi Mohsin Ali Jongseo Lee Matthias Humt ... R. Roscher Muhammad Shahzad Wen Yang R. Bamler Xiaoxiang Zhu BDL UQCV OOD 66 1,112 0 07 Jul 2021
On the Practicality of Deterministic Epistemic Uncertainty Janis Postels Mattia Segu Tao Sun Luca Sieber Luc Van Gool Feng Yu Federico Tombari UQCV 38 60 0 01 Jul 2021
Fast whole-slide cartography in colon cancer histology using superpixels and CNN classification Frauke Wilm M. Benz Volker Bruns Serop Baghdadlian Jakob Dexl ... Thomas Wittenberg S. Merkel A. Hartmann Markus Eckstein C. Geppert 27 5 0 30 Jun 2021
Graceful Degradation and Related Fields J. Dymond 36 4 0 21 Jun 2021
Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safety Sebastian Houben Stephanie Abrecht Maram Akila Andreas Bär Felix Brockherde ... Serin Varghese Michael Weber Sebastian J. Wirkert Tim Wirtz Matthias Woehrle AAML 13 58 0 29 Apr 2021
A Survey on Assessing the Generalization Envelope of Deep Neural Networks: Predictive Uncertainty, Out-of-distribution and Adversarial Samples Julia Lust Alexandru Paul Condurache UQCV AAML AI4CE 29 8 0 21 Aug 2020
On the Difficulty of Membership Inference Attacks Shahbaz Rezaei Xin Liu MIACV 22 13 0 27 May 2020
Detection and Retrieval of Out-of-Distribution Objects in Semantic Segmentation Philipp Oberdiek Matthias Rottmann G. Fink 31 30 0 14 May 2020
Anomalous Example Detection in Deep Learning: A Survey Saikiran Bulusu B. Kailkhura Bo Li P. Varshney D. Song AAML 28 47 0 16 Mar 2020
Detection of False Positive and False Negative Samples in Semantic Segmentation Matthias Rottmann Kira Maag Robin Shing Moon Chan Fabian Hüger Peter Schlicht Hanno Gottschalk UQCV 28 23 0 08 Dec 2019
Time-Dynamic Estimates of the Reliability of Deep Semantic Segmentation Networks Kira Maag Matthias Rottmann Hanno Gottschalk 29 34 0 12 Nov 2019
Accurate Layerwise Interpretable Competence Estimation Vickram Rajendran Will LeVine 25 10 0 24 Oct 2019
Density estimation in representation space to predict model uncertainty Tiago Ramalho M. Corbalan UQCV BDL 16 38 0 20 Aug 2019
Uncertainty Measures and Prediction Quality Rating for the Semantic Segmentation of Nested Multi Resolution Street Scene Images Matthias Rottmann Marius Schubert UQCV 27 38 0 09 Apr 2019
Prediction Error Meta Classification in Semantic Segmentation: Detection via Aggregated Dispersion Measures of Softmax Probabilities Matthias Rottmann Pascal Colling Thomas-Paul Hack Robin Shing Moon Chan Fabian Hüger Peter Schlicht Hanno Gottschalk UQCV 14 81 0 01 Nov 2018
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 359 5,849 0 08 Jul 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 287 9,167 0 06 Jun 2015