Results 151 to 160 of about 834,629 (316)
A fixed point theorem for contraction mappings in a uniformly convex normed space [PDF]
Shouro Kasahara
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Mapping uncertainty using differentiable programming
Abstract Uncertainty quantification (UQ) and propagation is a ubiquitous challenge in science, permeating our field in a general fashion, and its importance cannot be overstated. Recently, the commoditization of differentiable programming, motivated by the development of machine learning, has allowed easier access to tools for evaluating derivatives of
Victor Alves+3 more
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Fixed point theorems in probabilistic analysis [PDF]
A. T. Bharucha-Reid
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Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley +1 more source
A fixed point theorem for families on nonexpansive mappings [PDF]
Teck Cheong Lim
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Flexible Memory: Progress, Challenges, and Opportunities
Flexible memory technology is crucial for flexible electronics integration. This review covers its historical evolution, evaluates rigid systems, proposes a flexible memory framework based on multiple mechanisms, stresses material design's role, presents a coupling model for performance optimization, and points out future directions.
Ruizhi Yuan+5 more
wiley +1 more source
Joint Situational Assessment‐Hierarchical Decision‐Making Framework for Maneuver Intent Decisions
This study introduces a new framework for decision‐making in unmanned combat aerial vehicles (UCAVs), integrating graph convolutional networks and hierarchical reinforcement learning (HRL). The method tackles adopts a curriculum‐based training approach guided by cross‐entropy rewards.
Ruihai Chen+4 more
wiley +1 more source