Selective Classification Via Neural Network Training Dynamics

26 May 2022

Papers citing "Selective Classification Via Neural Network Training Dynamics"

22 / 22 papers shown

Title
Protecting against simultaneous data poisoning attacks Neel Alex Shoaib Ahmed Siddiqui Amartya Sanyal David M. Krueger AAML 27 1 0 23 Aug 2024
Confidence-aware Contrastive Learning for Selective Classification Yu-Chang Wu Shen-Huan Lyu Haopu Shang Xiangyu Wang Chao Qian 24 3 0 07 Jun 2024
To Believe or Not to Believe Your LLM Yasin Abbasi-Yadkori Ilja Kuzborskij András György Csaba Szepesvári UQCV 53 39 0 04 Jun 2024
Selective Explanations Lucas Monteiro Paes Dennis L. Wei Flavio du Pin Calmon FAtt 17 0 0 29 May 2024
Conformal Alignment: Knowing When to Trust Foundation Models with Guarantees Yu Gui Ying Jin Zhimei Ren MedIm 27 18 0 16 May 2024
Attacking Bayes: On the Adversarial Robustness of Bayesian Neural Networks Yunzhen Feng Tim G. J. Rudner Nikolaos Tsilivis Julia Kempe AAML BDL 26 1 0 27 Apr 2024
Mitigating LLM Hallucinations via Conformal Abstention Yasin Abbasi-Yadkori Ilja Kuzborskij David Stutz András György Adam Fisch ... Wei-Hung Weng Yao-Yuan Yang Csaba Szepesvári A. Cemgil Nenad Tomašev HILM 24 12 0 04 Apr 2024
LTAU-FF: Loss Trajectory Analysis for Uncertainty in Atomistic Force Fields Joshua A. Vita Amit Samanta Fei Zhou Vincenzo Lordi 8 2 0 01 Feb 2024
Function-Space Regularization in Neural Networks: A Probabilistic Perspective Tim G. J. Rudner Sanyam Kapoor Shikai Qiu A. Wilson 24 12 0 28 Dec 2023
Advancing Perception in Artificial Intelligence through Principles of Cognitive Science Palaash Agrawal Cheston Tan Heena Rathore 27 1 0 13 Oct 2023
Gradients Look Alike: Sensitivity is Often Overestimated in DP-SGD Anvith Thudi Hengrui Jia Casey Meehan Ilia Shumailov Nicolas Papernot 4 3 0 01 Jul 2023
Training Private Models That Know What They Don't Know Stephan Rabanser Anvith Thudi Abhradeep Thakurta Krishnamurthy Dvijotham Nicolas Papernot 6 7 0 28 May 2023
Distilling BlackBox to Interpretable models for Efficient Transfer Learning Shantanu Ghosh K. Yu Kayhan Batmanghelich 9 3 0 26 May 2023
ASPEST: Bridging the Gap Between Active Learning and Selective Prediction Jiefeng Chen Jinsung Yoon Sayna Ebrahimi Sercan Ö. Arik S. Jha Tomas Pfister 23 1 0 07 Apr 2023
Tackling Shortcut Learning in Deep Neural Networks: An Iterative Approach with Interpretable Models Shantanu Ghosh K. Yu Forough Arabshahi Kayhan Batmanghelich 25 2 0 20 Feb 2023
Beyond Distribution Shift: Spurious Features Through the Lens of Training Dynamics Nihal Murali A. Puli Ke Yu Rajesh Ranganath Kayhan Batmanghelich AAML 22 7 0 18 Feb 2023
Selective classification using a robust meta-learning approach Nishant Jain Karthikeyan Shanmugam Pradeep Shenoy OOD 13 2 0 12 Dec 2022
Metadata Archaeology: Unearthing Data Subsets by Leveraging Training Dynamics Shoaib Ahmed Siddiqui Nitarshan Rajkumar Tegan Maharaj David M. Krueger Sara Hooker 20 27 0 20 Sep 2022
Tubes Among Us: Analog Attack on Automatic Speaker Identification Shimaa Ahmed Yash R. Wani Ali Shahin Shamsabadi Mohammad Yaghini Ilia Shumailov Nicolas Papernot Kassem Fawaz AAML 25 3 0 06 Feb 2022
Estimating Example Difficulty Using Variance of Gradients Chirag Agarwal Daniel D'souza Sara Hooker 190 103 0 26 Aug 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 268 5,635 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 245 9,042 0 06 Jun 2015