Learning to Maximize Mutual Information for Dynamic Feature Selection

Learning to Maximize Mutual Information for Dynamic Feature Selection

2 January 2023

Papers citing "Learning to Maximize Mutual Information for Dynamic Feature Selection"

11 / 11 papers shown

Title
FRET: Feature Redundancy Elimination for Test Time Adaptation Linjing You Jiabao Lu Xiayuan Huang Xiangli Nie 17 0 0 15 May 2025
From Pixels to Perception: Interpretable Predictions via Instance-wise Grouped Feature Selection Moritz Vandenhirtz Julia E. Vogt 43 0 0 09 May 2025
LLM-Rubric: A Multidimensional, Calibrated Approach to Automated Evaluation of Natural Language Texts Helia Hashemi J. Eisner Corby Rosset Benjamin Van Durme Chris Kedzie 68 2 0 03 Jan 2025
Partial Information Decomposition for Data Interpretability and Feature Selection Charles Westphal Stephen Hailes Mirco Musolesi 40 0 0 29 May 2024
Learning to Maximize Mutual Information for Chain-of-Thought Distillation Xin Chen Hanxian Huang Yanjun Gao Yi Wang Jishen Zhao Ke Ding 45 12 0 05 Mar 2024
Information-Theoretic State Variable Selection for Reinforcement Learning Charles Westphal Stephen Hailes Mirco Musolesi 26 3 0 21 Jan 2024
Variational Information Pursuit with Large Language and Multimodal Models for Interpretable Predictions Kwan Ho Ryan Chan Aditya Chattopadhyay B. Haeffele René Vidal 42 0 0 24 Aug 2023
Estimating Conditional Mutual Information for Dynamic Feature Selection S. Gadgil Ian Covert Su-In Lee 34 3 0 05 Jun 2023
Have We Learned to Explain?: How Interpretability Methods Can Learn to Encode Predictions in their Interpretations N. Jethani Mukund Sudarshan Yindalon Aphinyanagphongs Rajesh Ranganath FAtt 82 69 0 02 Mar 2021
Active Information Acquisition He He Paul Mineiro Nikos Karampatziakis 65 18 0 05 Feb 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 287 9,156 0 06 Jun 2015