iDECODe: In-distribution Equivariance for Conformal Out-of-distribution
Detection

iDECODe: In-distribution Equivariance for Conformal Out-of-distribution Detection

AAAI Conference on Artificial Intelligence (AAAI), 2022

7 January 2022

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Papers citing "iDECODe: In-distribution Equivariance for Conformal Out-of-distribution Detection"

16 / 16 papers shown

Title
Conformal Information Pursuit for Interactively Guiding Large Language Models Kwan Ho Ryan Chan Yuyan Ge Edgar Dobriban Hamed Hassani René Vidal 159 2 0 04 Jul 2025
Monitor and Recover: A Paradigm for Future Research on Distribution Shift in Learning-Enabled Cyber-Physical SystemsInternational Conference on Cyber-Physical Systems (ICCPS), 2025 Vivian Lin Insup Lee 268 0 0 18 Apr 2025
Removing Geometric Bias in One-Class Anomaly Detection with Adaptive Feature PerturbationIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2025 Romain Hermary Vincent Gaudillière Abd El Rahman Shabayek Djamila Aouada AAML 338 1 0 07 Mar 2025
Addressing Uncertainty in LLMs to Enhance Reliability in Generative AI R. Kaur Colin Samplawski Adam Cobb Anirban Roy Brian Matejek ... Daniel Elenius Alexander M. Berenbeim John A. Pavlik Nathaniel D. Bastian Susmit Jha 328 11 0 04 Nov 2024
Controlling FSR in Selective Classification Guanlan Zhao Zhonggen Su 367 1 0 07 Nov 2023
Memory-Consistent Neural Networks for Imitation LearningInternational Conference on Learning Representations (ICLR), 2023 Kaustubh Sridhar Souradeep Dutta Dinesh Jayaraman James Weimer Insup Lee 278 15 0 09 Oct 2023
Neuro Symbolic Reasoning for Planning: Counterexample Guided Inductive Synthesis using Large Language Models and Satisfiability Solving Matthias Zeller Susmit Jha Patrick Lincoln Jens Behley Alvaro Velasquez Rickard Ewetz C. Stachniss LRM 179 9 0 28 Sep 2023
Neural Stochastic Differential Equations for Robust and Explainable Analysis of Electromagnetic Unintended Radiated Emissions Sumit Kumar Jha Susmit Jha Rickard Ewetz Alvaro Velasquez 173 2 0 27 Sep 2023
Detection of Adversarial Physical Attacks in Time-Series Image Data Ramneet Kaur Y. Kantaros Wenwen Si James Weimer Insup Lee AAML 156 3 0 27 Apr 2023
Conformal Prediction Regions for Time Series using Linear Complementarity ProgrammingAAAI Conference on Artificial Intelligence (AAAI), 2023 Matthew Cleaveland Insup Lee George J. Pappas Lars Lindemann 634 44 0 03 Apr 2023
Boosting Out-of-Distribution Detection with Multiple Pre-trained Models Feng Xue Zi He Chuanlong Xie Falong Tan Zhenguo Li OODD 328 7 0 24 Dec 2022
Targeted Adversarial Attacks against Neural Network Trajectory PredictorsConference on Learning for Dynamics & Control (L4DC), 2022 Kai Liang Tan Jun Wang Y. Kantaros AAML 198 25 0 08 Dec 2022
In What Ways Are Deep Neural Networks Invariant and How Should We Measure This?Neural Information Processing Systems (NeurIPS), 2022 Henry Kvinge Tegan H. Emerson Grayson Jorgenson Scott Vasquez T. Doster Jesse D. Lew 186 12 0 07 Oct 2022
Multiple Testing Framework for Out-of-Distribution Detection A. Magesh Venugopal V. Veeravalli Anirban Roy Susmit Jha OODD 350 5 0 20 Jun 2022
PAC-Wrap: Semi-Supervised PAC Anomaly DetectionKnowledge Discovery and Data Mining (KDD), 2022 Shuo Li Xiayan Ji Guang Cheng O. Sokolsky Insup Lee 253 20 0 22 May 2022
Generalized Out-of-Distribution Detection: A SurveyInternational Journal of Computer Vision (IJCV), 2021 Jingkang Yang Kaiyang Zhou Shouqing Yang Ziwei Liu 728 1,202 0 21 Oct 2021