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1812.05720
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Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem
13 December 2018
Matthias Hein
Maksym Andriushchenko
Julian Bitterwolf
OODD
Re-assign community
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Papers citing
"Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem"
50 / 349 papers shown
Title
In or Out? Fixing ImageNet Out-of-Distribution Detection Evaluation
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Are Deep Neural Networks Adequate Behavioural Models of Human Visual Perception?
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Robert Geirhos
61
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Monitoring and Adapting ML Models on Mobile Devices
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Zixi Wang
Lauren Hong
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4
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Great Models Think Alike: Improving Model Reliability via Inter-Model Latent Agreement
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Promises and Pitfalls of the Linearized Laplace in Bayesian Optimization
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Sayna Ebrahimi
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Tomas Pfister
113
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Diffusion Denoised Smoothing for Certified and Adversarial Robust Out-Of-Distribution Detection
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Daniel Korth
J. Lorenz
Karsten Roscher
Stephan Guennemann
60
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0
27 Mar 2023
SIO: Synthetic In-Distribution Data Benefits Out-of-Distribution Detection
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Nathan Inkawhich
Randolph Linderman
R. Luley
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H. Li
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71
1
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Bridging Precision and Confidence: A Train-Time Loss for Calibrating Object Detection
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Salman Khan
Fahad Shahbaz Khan
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86
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0
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ProtoCon: Pseudo-label Refinement via Online Clustering and Prototypical Consistency for Efficient Semi-supervised Learning
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Ehsan Abbasnejad
Hamid Rezatofighi
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74
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0
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On the Calibration and Uncertainty with Pólya-Gamma Augmentation for Dialog Retrieval Models
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116
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InPL: Pseudo-labeling the Inliers First for Imbalanced Semi-supervised Learning
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83
13
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Non-Parametric Outlier Synthesis
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Xuefeng Du
Xiaojin Zhu
Yixuan Li
OODD
97
108
0
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DeepLens: Interactive Out-of-distribution Data Detection in NLP Models
D. Song
Zhijie Wang
Yuheng Huang
Lei Ma
Tianyi Zhang
56
4
0
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Uncertainty Injection: A Deep Learning Method for Robust Optimization
W. Cui
Wei Yu
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OOD
34
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VRA: Variational Rectified Activation for Out-of-distribution Detection
Ming Xu
Zheng Lian
B. Liu
Jianhua Tao
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43
10
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Fixing Overconfidence in Dynamic Neural Networks
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Andrea Pilzer
Le Yang
Arno Solin
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127
16
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Learning to Scale Temperature in Masked Self-Attention for Image Inpainting
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Yuan Zeng
Yi Gong
83
2
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Better Diffusion Models Further Improve Adversarial Training
Zekai Wang
Tianyu Pang
Chao Du
Min Lin
Weiwei Liu
Shuicheng Yan
DiffM
106
228
0
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Energy-based Out-of-Distribution Detection for Graph Neural Networks
Qitian Wu
Yiting Chen
Chenxiao Yang
Junchi Yan
OODD
129
68
0
06 Feb 2023
Trust, but Verify: Using Self-Supervised Probing to Improve Trustworthiness
Ailin Deng
Shen Li
Miao Xiong
Zhirui Chen
Bryan Hooi
66
4
0
06 Feb 2023
Interpretable Out-Of-Distribution Detection Using Pattern Identification
Romain Xu-Darme
Julien Girard-Satabin
Darryl Hond
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Zakaria Chihani
OODD
65
4
0
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Key Feature Replacement of In-Distribution Samples for Out-of-Distribution Detection
Jaeyoung Kim
Seo Taek Kong
Dongbin Na
Kyu-Hwan Jung
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41
4
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26 Dec 2022
Boosting Out-of-Distribution Detection with Multiple Pre-trained Models
Feng Xue
Zi He
Chuanlong Xie
Falong Tan
Zhenguo Li
OODD
123
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0
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Rainproof: An Umbrella To Shield Text Generators From Out-Of-Distribution Data
Maxime Darrin
Pablo Piantanida
Pierre Colombo
OODD
222
15
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18 Dec 2022
Improving group robustness under noisy labels using predictive uncertainty
Dongpin Oh
Dae Lee
Jeunghyun Byun
Bonggun Shin
UQCV
60
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0
14 Dec 2022
Spurious Features Everywhere -- Large-Scale Detection of Harmful Spurious Features in ImageNet
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Maximilian Augustin
Valentyn Boreiko
Matthias Hein
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134
32
0
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Self-training via Metric Learning for Source-Free Domain Adaptation of Semantic Segmentation
Ibrahim Batuhan Akkaya
U. Halici
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94
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08 Dec 2022
Block Selection Method for Using Feature Norm in Out-of-distribution Detection
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Sungho Shin
Seongju Lee
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83
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Rethinking Out-of-Distribution Detection From a Human-Centric Perspective
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Rongxin Jiang
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Yao-wu Chen
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70
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Mısra Yavuz
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99
47
0
25 Nov 2022
Delving into Out-of-Distribution Detection with Vision-Language Representations
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Ziyan Cai
Jiuxiang Gu
Yiyou Sun
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130
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Promises and Pitfalls of Threshold-based Auto-labeling
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Quantifying Model Uncertainty for Semantic Segmentation using Operators in the RKHS
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73
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Watermarking for Out-of-distribution Detection
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88
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On double-descent in uncertainty quantification in overparametrized models
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163
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Augmentation by Counterfactual Explanation -- Fixing an Overconfident Classifier
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122
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Exploring Predictive Uncertainty and Calibration in NLP: A Study on the Impact of Method & Data Scarcity
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267
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Enhancing Out-of-Distribution Detection in Natural Language Understanding via Implicit Layer Ensemble
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Sang-goo Lee
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119
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Packed-Ensembles for Efficient Uncertainty Estimation
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Gianni Franchi
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145
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Prediction Calibration for Generalized Few-shot Semantic Segmentation
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OpenOOD: Benchmarking Generalized Out-of-Distribution Detection
Jingkang Yang
Pengyun Wang
Dejian Zou
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...
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Dan Hendrycks
Yixuan Li
Ziwei Liu
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Robust Models are less Over-Confident
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Curved Representation Space of Vision Transformers
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Jongseok Lee
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Boosting Out-of-distribution Detection with Typical Features
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YueFeng Chen
Chuanlong Xie
Xiaodan Li
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Bolun Zheng
Yao-wu Chen
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104
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