Many mathematical models utilize limit processes. Continuous functions and the calculus, differential equations and topology, all are based on limits and continuity. However, when we perform measurements and computations, we can achieve only approximate results. In some cases, this discrepancy between theoretical schemes and practical actions changes drastically outcomes of a research and decision-making resulting in uncertainty of knowledge. In the paper, a mathematical approach to such kind of uncertainty, which emerges in computation and measurement, is suggested on the base of the concept of a fuzzy limit. A mathematical technique is developed for differential models with uncertainty. To take into account the intrinsic uncertainty of a model, it is suggested to use fuzzy derivatives instead of conventional derivatives of functions in this model.
Trust Your Robots! Predictive Uncertainty Estimation of Neural Networks with Sparse Gaussian Processes
German Aerospace Center (DLR)（德国航空航天中心）；Karlsruhe Institute of Technology (KIT)（卡尔斯鲁厄理工学院）；Technical University of Munich (TUM)（慕尼黑工业大学）；ETH Zürich (ETHZ)（苏黎世联邦理工学院）
Meta-learning to Calibrate Gaussian Processes with Deep Kernels for Regression Uncertainty Estimation
NTT Communication Science Laboratories, NTT Corporation（NTT集团NTT通信科学实验室）；NTT Computer and Data Science Laboratories, NTT Corporation（NTT集团NTT计算机与数据科学实验室）
Planning with Information-Processing Constraints and Model Uncertainty in Markov Decision Processes
Max Planck Institute for Intelligent Systems（马克斯·普朗克智能系统研究所）；Max Planck Institute for Biological Cybernetics（马克斯·普朗克生物 cybernetics 研究所）；Graduate Training Centre for Neuroscience（神经科学研究生培训中心）
Towards interval uncertainty propagation control in bivariate aggregation processes and the introduction of width-limited interval-valued overlap functions
Universidad Pública de Navarra（纳瓦拉公立大学）；Universidade Federal do Rio Grande（里奥格兰德联邦大学）；Universidade Federal do Rio Grande do Norte（北里奥格兰德联邦大学）
Overlap functions are a class of aggregation functions that measure the overlapping degree between two values. Interval-valued overlap functions were defined as an extension to express the overlapping of interval-valued data, and they have been usually applied when there is uncertainty regarding the assignment of membership degrees. The choice of a total order for intervals can be significant, which motivated the recent developments on interval-valued aggregation functions and interval-valued overlap functions that are increasing to a given admissible order, that is, a total order that refines…
