Exploring the Trade-off Between Model Performance and Explanation Plausibility of Text Classifiers Using Human Rationalesby…
Composite Bayesian Optimization In Function Spaces Using NEON – Neural Epistemic Operator Networksby Leonardo Ferreira…
Methodology for Interpretable Reinforcement Learning for Optimizing Mechanical Ventilationby Joo Seung Lee, Malini Mahendra, Anil…
Deep Learning-Based Weather-Related Power Outage Prediction with Socio-Economic and Power Infrastructure Databy Xuesong Wang, Nina…
Theoretical and Empirical Insights into the Origins of Degree Bias in Graph Neural Networksby Arjun…
Uncertainty in Language Models: Assessment through Rank-Calibrationby Xinmeng Huang, Shuo Li, Mengxin Yu, Matteo Sesia,…
Information-Theoretic Generalization Bounds for Deep Neural Networksby Haiyun He, Christina Lee Yu, Ziv GoldfeldFirst submitted…
Future-Proofing Class-Incremental Learningby Quentin Jodelet, Xin Liu, Yin Jun Phua, Tsuyoshi MurataFirst submitted to arxiv…
Goldfish: An Efficient Federated Unlearning Frameworkby Houzhe Wang, Xiaojie Zhu, Chi Chen, Paulo Esteves-VerÃssimoFirst submitted…
HiMAL: A Multimodal Hierarchical Multi-task Auxiliary Learning framework for predicting and explaining Alzheimer disease progressionby…