:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	de Souza, Victor F. Lopes, Bakhti, Karima, Ramdani, Sofiane, Mottet, Denis, Imoussaten, Abdelhak
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2507.12192
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Relevance-Aware Thresholding in Online Conformal Prediction for Time Series
by: Dupuy, Théo, et al.
Published: (2025)

eDOC: Explainable Decoding Out-of-domain Cell Types with Evidential Learning
by: Wu, Chaochen, et al.
Published: (2024)

Assessing Time Series Correlation Significance: A Parametric Approach with Application to Physiological Signals
by: Medrano, Johan, et al.
Published: (2024)

Evidential uncertainty sampling for active learning
by: Hoarau, Arthur, et al.
Published: (2023)

Uncertainty Regularized Evidential Regression
by: Ye, Kai, et al.
Published: (2024)

Evidential Transformation Network: Turning Pretrained Models into Evidential Models for Post-hoc Uncertainty Estimation
by: Chun, Yongchan, et al.
Published: (2026)

Uncertainty Estimation by Flexible Evidential Deep Learning
by: Yoon, Taeseong, et al.
Published: (2025)

Evidential Uncertainty Probes for Graph Neural Networks
by: Yu, Linlin, et al.
Published: (2025)

Uncertainty Quantification of Wind Gust Predictions in the Northeast United States: An Evidential Neural Network and Explainable Artificial Intelligence Approach
by: Jahan, Israt, et al.
Published: (2025)

Graph Evidential Learning for Anomaly Detection
by: Wei, Chunyu, et al.
Published: (2025)

Calibrating LLMs with Information-Theoretic Evidential Deep Learning
by: Li, Yawei, et al.
Published: (2025)

Efficient Uncertainty in LLMs through Evidential Knowledge Distillation
by: Nemani, Lakshmana Sri Harsha, et al.
Published: (2025)

Explainable Clustering Beyond Worst-Case Guarantees
by: Fleissner, Maximilian, et al.
Published: (2024)

Uncertainty Estimation by Density Aware Evidential Deep Learning
by: Yoon, Taeseong, et al.
Published: (2024)

GEM-FI: Gated Evidential Mixtures with Fisher Modulation
by: Mohammed, Marco Mustafa, et al.
Published: (2026)

Evidential time-to-event prediction with calibrated uncertainty quantification
by: Huang, Ling, et al.
Published: (2024)

If You Want to Be Robust, Be Wary of Initialization
by: Ennadir, Sofiane, et al.
Published: (2025)

SPINEX-Clustering: Similarity-based Predictions with Explainable Neighbors Exploration for Clustering Problems
by: Naser, MZ, et al.
Published: (2024)

Contrastive Explainable Clustering with Differential Privacy
by: Nguyen, Dung, et al.
Published: (2024)

Equivariant Evidential Deep Learning for Interatomic Potentials
by: Wang, Zhongyao, et al.
Published: (2026)

Explainable AI for microseismic event detection
by: Abdullin, Ayrat, et al.
Published: (2025)

Overcoming Non-stationary Dynamics with Evidential Proximal Policy Optimization
by: Akgül, Abdullah, et al.
Published: (2025)

Fairness-Aware Multi-view Evidential Learning with Adaptive Prior
by: Chen, Haishun, et al.
Published: (2025)

Improving Group Robustness on Spurious Correlation via Evidential Alignment
by: Ye, Wenqian, et al.
Published: (2025)

Are Uncertainty Quantification Capabilities of Evidential Deep Learning a Mirage?
by: Shen, Maohao, et al.
Published: (2024)

Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events
by: Khot, Ayush, et al.
Published: (2024)

Towards Explainable Deep Clustering for Time Series Data
by: Schlegel, Udo, et al.
Published: (2025)

Radius selection using kernel density estimation for the computation of nonlinear measures
by: Medrano, Johan, et al.
Published: (2024)

Evidential Physics-Informed Neural Networks
by: Tan, Hai Siong, et al.
Published: (2025)

Joint Embeddings Go Temporal
by: Ennadir, Sofiane, et al.
Published: (2025)

Fairness-informed Pareto Optimization : An Efficient Bilevel Framework
by: Tanji, Sofiane, et al.
Published: (2026)

Evidential Neural Radiance Fields
by: Duan, Ruxiao, et al.
Published: (2026)

Sensitivity Curve Maximization: Attacking Robust Aggregators in Distributed Learning
by: Schroth, Christian A., et al.
Published: (2024)

A Simple and Yet Fairly Effective Defense for Graph Neural Networks
by: Ennadir, Sofiane, et al.
Published: (2024)

Rough Sets for Explainability of Spectral Graph Clustering
by: Starosta, Bartłomiej, et al.
Published: (2025)

Evidential Physics-Informed Neural Networks for Scientific Discovery
by: Tan, Hai Siong, et al.
Published: (2025)

Revisiting Essential and Nonessential Settings of Evidential Deep Learning
by: Chen, Mengyuan, et al.
Published: (2024)

Enhanced Federated Anomaly Detection Through Autoencoders Using Summary Statistics-Based Thresholding
by: Laridi, Sofiane, et al.
Published: (2024)

Weakly-Supervised Residual Evidential Learning for Multi-Instance Uncertainty Estimation
by: Liu, Pei, et al.
Published: (2024)

Detecting Misbehaviors of Large Vision-Language Models by Evidential Uncertainty Quantification
by: Huang, Tao, et al.
Published: (2026)