output
20092026
most citedA Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges

2.7k citations

31 papers

cs.LG2026★ 3 cited

Reinforcement Learning-Guided NSGA-II Enhanced with Gray Relational Coefficient for Multi-Objective Optimization: Application to NASDAQ Portfolio Optimization

Zhiyuan Wang, Qinxu Ding, Ding Ding +4

In modern financial markets, decision-makers increasingly rely on quantitative methods to navigate complex trade-offs among multiple, often conflicting objectives. This paper addre…

math.OC2026★ 9 cited

Subjective-Objective Median-based Importance Technique (SOMIT) to Aid Multi-Criteria Renewable Energy Evaluation

Ding Ding, Yang Li, Poh Ling Neo +2

Accelerating the renewable energy transition requires informed decision-making that accounts for the diverse financial, technical, environmental, and social trade-offs across diffe…

cs.SE2025

MINES: Explainable Anomaly Detection through Web API Invariant Inference

Wenjie Zhang, Yun Lin, Chun Fung Amos Kwok +5

Detecting the anomalies of web applications, important infrastructures for running modern companies and governments, is crucial for providing reliable web services. Many modern web…

cond-mat.quant-gas2025★ 1 cited

Josephson Dynamics in 2D Ring-shaped Condensates

Koon Siang Gan, Vijay Pal Singh, Luigi Amico +1

We investigate Josephson transport in a fully closed, two-dimensional superfluid circuit formed by a ring-shaped 87Rb Bose-Einstein condensate that contains two optical barriers ac…

nucl-th2025

Speed of sound of QCD matter at chiral crossover

Oleksii Ivanytskyi, David Blaschke, Gerd Röpke

Based on a generalized Beth-Uhlenbeck approach to thermodynamics of QCD motivated by cluster decomposition we present a unified equation of state of hot strongly interacting matter…

cs.AI2025★ 9 cited

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets

Patrick Stöckermann, Henning Südfeld, Alessandro Immordino +7

Benchmark datasets are crucial for evaluating approaches to scheduling or dispatching in the semiconductor industry during the development and deployment phases. However, commonly…