Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images

5 December 2014

Jeff Clune

Papers citing "Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images"

50 / 1,401 papers shown

Title
Adversarial attacks and defenses in explainable artificial intelligence: A survey Hubert Baniecki P. Biecek AAML 47 63 0 06 Jun 2023
Enhance Diffusion to Improve Robust Generalization Jianhui Sun Sanchit Sinha Aidong Zhang 34 4 0 05 Jun 2023
DOS: Diverse Outlier Sampling for Out-of-Distribution Detection Wenyu Jiang Hao Cheng Mingcai Chen Chongjun Wang Hongxin Wei OOD OODD 24 9 0 03 Jun 2023
Out-of-distribution forgetting: vulnerability of continual learning to intra-class distribution shift Liangxuan Guo Yang Chen Shan Yu OODD CLL 30 2 0 01 Jun 2023
T2FNorm: Extremely Simple Scaled Train-time Feature Normalization for OOD Detection Sudarshan Regmi Bibek Panthi S. Dotel P. Gyawali Danail Stoynov Binod Bhattarai OODD 40 3 0 28 May 2023
Amplification trojan network: Attack deep neural networks by amplifying their inherent weakness Zhan Hu Jun Zhu Bo Zhang Xiaolin Hu AAML 32 2 0 28 May 2023
The Curse of Recursion: Training on Generated Data Makes Models Forget Ilia Shumailov Zakhar Shumaylov Yiren Zhao Y. Gal Nicolas Papernot Ross J. Anderson DiffM 31 282 0 27 May 2023
SELFOOD: Self-Supervised Out-Of-Distribution Detection via Learning to Rank Dheeraj Mekala Adithya Samavedhi Chengyu Dong Jingbo Shang OODD 29 2 0 24 May 2023
Is Fine-tuning Needed? Pre-trained Language Models Are Near Perfect for Out-of-Domain Detection Rheeya Uppaal Junjie Hu Yixuan Li OODD 119 33 0 22 May 2023
DAP: A Dynamic Adversarial Patch for Evading Person Detectors Amira Guesmi Ruitian Ding Muhammad Abdullah Hanif Ihsen Alouani Mohamed Bennai AAML 36 25 0 19 May 2023
Noise robust neural network architecture Yunuo Xiong Hongwei Xiong 24 1 0 16 May 2023
FLARE: Detection and Mitigation of Concept Drift for Federated Learning based IoT Deployments The-Yuan Chow Usman Raza Ioannis Mavromatis Aftab Khan 31 4 0 15 May 2023
Monitoring and Adapting ML Models on Mobile Devices Wei Hao Zixi Wang Lauren Hong Lingxi Li Nader Karayanni Chengzhi Mao Junfeng Yang Asaf Cidon OffRL 27 4 0 12 May 2023
Sparsifying Bayesian neural networks with latent binary variables and normalizing flows Lars Skaaret-Lund G. Storvik A. Hubin BDL UQCV 30 3 0 05 May 2023
Cluster Flow: how a hierarchical clustering layer make allows deep-NNs more resilient to hacking, more human-like and easily implements relational reasoning E. Gale Oliver Matthews 3DH 22 0 0 27 Apr 2023
QuantProb: Generalizing Probabilities along with Predictions for a Pre-trained Classifier Aditya Challa Snehanshu Saha S. Dhavala UQCV 33 2 0 25 Apr 2023
Uncertainty Propagation in Node Classification Zhao Xu Carolin (Haas) Lawrence Ammar Shaker Raman Siarheyeu BDL UQCV 50 2 0 03 Apr 2023
Enhancing Multiple Reliability Measures via Nuisance-extended Information Bottleneck Jongheon Jeong Sihyun Yu Hankook Lee Jinwoo Shin AAML 46 0 0 24 Mar 2023
ProtoCon: Pseudo-label Refinement via Online Clustering and Prototypical Consistency for Efficient Semi-supervised Learning Islam Nassar Munawar Hayat Ehsan Abbasnejad Hamid Rezatofighi Gholamreza Haffari 40 17 0 22 Mar 2023
Wasserstein Loss for Semantic Editing in the Latent Space of GANs Perla Doubinsky Nicolas Audebert M. Crucianu Hervé Le Borgne GAN 19 1 0 22 Mar 2023
AUTO: Adaptive Outlier Optimization for Test-Time OOD Detection Puning Yang Jian Liang Jie Cao Ran He 41 12 0 22 Mar 2023
The Representational Status of Deep Learning Models Eamon Duede 31 0 0 21 Mar 2023
Uncertainty-Aware Optimal Transport for Semantically Coherent Out-of-Distribution Detection Fan Lu Kai Zhu Wei Zhai Kecheng Zheng Yang Cao UQCV 46 20 0 18 Mar 2023
Finding Competence Regions in Domain Generalization Jens Müller Stefan T. Radev R. Schmier Felix Dräxler Carsten Rother Ullrich Kothe 29 4 0 17 Mar 2023
Explainable GeoAI: Can saliency maps help interpret artificial intelligence's learning process? An empirical study on natural feature detection Chia-Yu Hsu Wenwen Li AAML FAtt 19 34 0 16 Mar 2023
Frequency-Modulated Point Cloud Rendering with Easy Editing Yi Zhang Xiaoyang Huang Bingbing Ni Teng Li Wenjun Zhang 41 13 0 14 Mar 2023
InPL: Pseudo-labeling the Inliers First for Imbalanced Semi-supervised Learning Zhuliang Yu Yin Li Yong Jae Lee 27 10 0 13 Mar 2023
Accurate Real-time Polyp Detection in Videos from Concatenation of Latent Features Extracted from Consecutive Frames H. Qadir Younghak Shin Jacob Bergsland I. Balasingham MedIm 16 3 0 10 Mar 2023
Adapting Contrastive Language-Image Pretrained (CLIP) Models for Out-of-Distribution Detection Nikolas Adaloglou Félix D. P. Michels Tim Kaiser M. Kollmann VLM 37 0 0 10 Mar 2023
Out-of-distribution Detection with Implicit Outlier Transformation Qizhou Wang Junjie Ye Feng Liu Quanyu Dai Marcus Kalander Tongliang Liu Jianye Hao Bo Han OODD 155 46 0 09 Mar 2023
Learning the Finer Things: Bayesian Structure Learning at the Instantiation Level Chase Yakaboski E. Santos 21 2 0 08 Mar 2023
A topological classifier to characterize brain states: When shape matters more than variance Aina Ferrà G. Cecchini Fritz-Pere Nobbe Fisas Carles Casacuberta I. Cos 23 2 0 07 Mar 2023
EscherNet 101 Christopher Funk Yanxi Liu 18 0 0 07 Mar 2023
Non-Parametric Outlier Synthesis Leitian Tao Xuefeng Du Xiaojin Zhu Yixuan Li OODD 28 98 0 06 Mar 2023
AdvART: Adversarial Art for Camouflaged Object Detection Attacks Amira Guesmi Ioan Marius Bilasco Mohamed Bennai Ihsen Alouani GAN AAML 47 20 0 03 Mar 2023
DeepLens: Interactive Out-of-distribution Data Detection in NLP Models D. Song Zhijie Wang Yuheng Huang Lei Ma Tianyi Zhang 32 4 0 02 Mar 2023
Average of Pruning: Improving Performance and Stability of Out-of-Distribution Detection Zhen Cheng Fei Zhu Xu-Yao Zhang Cheng-Lin Liu MoMe OODD 45 11 0 02 Mar 2023
Implicit Poisoning Attacks in Two-Agent Reinforcement Learning: Adversarial Policies for Training-Time Attacks Mohammad Mohammadi Jonathan Nöther Debmalya Mandal Adish Singla Goran Radanović AAML OffRL 35 9 0 27 Feb 2023
Novel Class Discovery: an Introduction and Key Concepts Colin Troisemaine V. Lemaire Stéphane Gosselin Alexandre Reiffers-Masson Joachim Flocon-Cholet Sandrine Vaton 50 21 0 22 Feb 2023
Gradient-based Wang-Landau Algorithm: A Novel Sampler for Output Distribution of Neural Networks over the Input Space Weitang Liu Ying-Wai Li Yi-Zhuang You Jingbo Shang 21 1 0 19 Feb 2023
Probabilistic Circuits That Know What They Don't Know Fabrizio G. Ventola Steven Braun Zhongjie Yu Martin Mundt Kristian Kersting UQCV TPM 32 7 0 13 Feb 2023
Human-Centric Multimodal Machine Learning: Recent Advances and Testbed on AI-based Recruitment Alejandro Peña Ignacio Serna Aythami Morales Julian Fierrez Alfonso Ortega Ainhoa Herrarte Manuel Alcántara J. Ortega-Garcia FaML 25 35 0 13 Feb 2023
Learning from Noisy Crowd Labels with Logics Zhijun Chen Hailong Sun Haoqian He Pengpeng Chen NoLa NAI 32 7 0 13 Feb 2023
Delving Deep into Simplicity Bias for Long-Tailed Image Recognition Xiu-Shen Wei Xuhao Sun Yang Shen Anqi Xu Peng Wang Faen Zhang 38 1 0 07 Feb 2023
Exploring and Exploiting Decision Boundary Dynamics for Adversarial Robustness Yuancheng Xu Yanchao Sun Micah Goldblum Tom Goldstein Furong Huang AAML 31 37 0 06 Feb 2023
Trust, but Verify: Using Self-Supervised Probing to Improve Trustworthiness Ailin Deng Shen Li Miao Xiong Zhirui Chen Bryan Hooi 24 4 0 06 Feb 2023
Asymmetric Certified Robustness via Feature-Convex Neural Networks Samuel Pfrommer Brendon G. Anderson Julien Piet Somayeh Sojoudi AAML 30 7 0 03 Feb 2023
Plugin estimators for selective classification with out-of-distribution detection Harikrishna Narasimhan A. Menon Wittawat Jitkrittum Surinder Kumar OODD 36 4 0 29 Jan 2023
SACDNet: Towards Early Type 2 Diabetes Prediction with Uncertainty for Electronic Health Records Tayyab Nasir M. K. Malik 13 2 0 12 Jan 2023
Do Bayesian Variational Autoencoders Know What They Don't Know? Misha Glazunov Apostolis Zarras UQCV BDL 28 5 0 29 Dec 2022