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2008.08030
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Gradients as a Measure of Uncertainty in Neural Networks
18 August 2020
Jinsol Lee
Ghassan AlRegib
UQCV
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Papers citing
"Gradients as a Measure of Uncertainty in Neural Networks"
48 / 48 papers shown
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Ctrl-U: Robust Conditional Image Generation via Uncertainty-aware Reward Modeling
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Out-of-Distribution Detection: A Task-Oriented Survey of Recent Advances
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YingSheng Wang
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Hang Yu
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Richard M. Bradford
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254
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Understanding the Dependence of Perception Model Competency on Regions in an Image
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Claire Tomlin
237
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Generalizable Physics-Informed Learning for Stochastic Safety-Critical Systems
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Yorie Nakahira
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Predictive Dynamic Fusion
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Bing Cao
Yinan Xia
Yi Ding
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Qinghua Hu
308
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07 Jun 2024
VOICE: Variance of Induced Contrastive Explanations to quantify Uncertainty in Neural Network Interpretability
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A Structured Review of Literature on Uncertainty in Machine Learning & Deep Learning
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Ramin Ramezani
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454
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Epistemic Uncertainty Quantification For Pre-trained Neural Network
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Qiang Ji
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217
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LUQ: Long-text Uncertainty Quantification for LLMs
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Fangyu Liu
Marco Basaldella
Nigel Collier
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29 Mar 2024
GROOD: GRadient-Aware Out-of-Distribution Detection
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Y. Pequignot
Paul Novello
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338
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22 Dec 2023
GAIA: Delving into Gradient-based Attribution Abnormality for Out-of-distribution Detection
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Junjie Li
Xiaoyang Qu
Jianzong Wang
Jiguang Wan
Jing Xiao
OODD
290
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16 Nov 2023
Revisiting Deep Ensemble for Out-of-Distribution Detection: A Loss Landscape Perspective
International Journal of Computer Vision (IJCV), 2023
Kun Fang
Qinghua Tao
Xiaolin Huang
Jie Yang
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335
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22 Oct 2023
GradOrth: A Simple yet Efficient Out-of-Distribution Detection with Orthogonal Projection of Gradients
Neural Information Processing Systems (NeurIPS), 2023
Sima Behpour
T. Doan
Xin Li
Wenbin He
Liangke Gou
Liu Ren
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340
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01 Aug 2023
GIT: Detecting Uncertainty, Out-Of-Distribution and Adversarial Samples using Gradients and Invariance Transformations
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Julia Lust
Alexandru Paul Condurache
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252
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Single-model uncertainty quantification in neural network potentials does not consistently outperform model ensembles
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Aik Rui Tan
S. Urata
Samuel Goldman
Johannes C. B. Dietschreit
Rafael Gómez-Bombarelli
BDL
324
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02 May 2023
Probing the Purview of Neural Networks via Gradient Analysis
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Jinsol Lee
Charles Lehman
Mohit Prabhushankar
Ghassan AlRegib
242
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06 Apr 2023
Delay-SDE-net: A deep learning approach for time series modelling with memory and uncertainty estimates
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A. Midtfjord
207
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14 Mar 2023
WDiscOOD: Out-of-Distribution Detection via Whitened Linear Discriminant Analysis
IEEE International Conference on Computer Vision (ICCV), 2023
Yiye Chen
Yunzhi Lin
Ruinian Xu
Patricio A. Vela
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326
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14 Mar 2023
Example Forgetting: A Novel Approach to Explain and Interpret Deep Neural Networks in Seismic Interpretation
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Ryan Benkert
Oluwaseun Joseph Aribido
Ghassan AlRegib
192
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24 Feb 2023
Gaussian Switch Sampling: A Second Order Approach to Active Learning
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Ryan Benkert
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Armin Pacharmi
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284
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16 Feb 2023
Generalized Uncertainty of Deep Neural Networks: Taxonomy and Applications
Chengyu Dong
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02 Feb 2023
Forgetful Active Learning with Switch Events: Efficient Sampling for Out-of-Distribution Data
International Conference on Information Photonics (ICIP), 2022
Ryan Benkert
Mohit Prabhushankar
Ghassan AlRegib
OODD
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206
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12 Jan 2023
Explaining Deep Models through Forgettable Learning Dynamics
International Conference on Information Photonics (ICIP), 2021
Ryan Benkert
Oluwaseun Joseph Aribido
Ghassan AlRegib
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156
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Explainable Machine Learning for Hydrocarbon Prospect Risking
Ahmad Mustafa
Ghassan AlRegib
195
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15 Dec 2022
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Lokesh Veeramacheneni
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233
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Introspective Learning : A Two-Stage Approach for Inference in Neural Networks
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337
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17 Sep 2022
TEDL: A Two-stage Evidential Deep Learning Method for Classification Uncertainty Quantification
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Wei Shen
Denis Xavier Charles
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251
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12 Sep 2022
Gradient-based Uncertainty for Monocular Depth Estimation
European Conference on Computer Vision (ECCV), 2022
Julia Hornauer
Vasileios Belagiannis
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290
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0
03 Aug 2022
Gradient-Based Adversarial and Out-of-Distribution Detection
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Mohit Prabhushankar
Ghassan AlRegib
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309
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16 Jun 2022
Open-Set Recognition with Gradient-Based Representations
International Conference on Information Photonics (ICIP), 2021
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Ghassan AlRegib
VLM
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162
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How Useful are Gradients for OOD Detection Really?
Conor Igoe
Youngseog Chung
I. Char
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OODD
236
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20 May 2022
Fine-grained TLS services classification with reject option
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161
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24 Feb 2022
Explanatory Paradigms in Neural Networks
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269
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Highlighting Object Category Immunity for the Generalization of Human-Object Interaction Detection
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Xinpeng Liu
Yong-Lu Li
Cewu Lu
252
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Gradient-based Novelty Detection Boosted by Self-supervised Binary Classification
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Jingbo Sun
Li Yang
Jiaxin Zhang
Frank Liu
M. Halappanavar
Deliang Fan
Yu Cao
216
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On the Importance of Gradients for Detecting Distributional Shifts in the Wild
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757
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203
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358
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25 Nov 2020
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