Results 101 to 110 of about 87,069 (296)
Koopman learning with episodic memory
Chaos: An Interdisciplinary Journal of Nonlinear ScienceKoopman operator theory has found significant success in learning models of complex, real-world dynamical systems, enabling prediction and control. The greater interpretability and lower computational costs of these models, compared to traditional machine learning methodologies, make Koopman learning an especially appealing approach.
William T. Redman +3 more
openaire +3 more sources
Advanced Science, EarlyView.This study presents an anatomical landmark‐guided DRL framework for autonomous wireless capsule endoscopy navigation. Using a lightweight edge‐contour‐depth fusion module, it achieves over 97% coverage across diverse gastric anatomies. To ensure reliability, a two‐stage sim‐to‐real pipeline with an adaptive dynamic programming controller mitigates ...
Haoxuan Wu +16 more
wiley +1 more source
Analog Weight Update Rule in Ferroelectric Hafnia, Using picoJoule Programming Pulses
Advanced Electronic Materials, EarlyView.Resistive, ferroelectric synaptic weights based on BEOL‐compatible hafnia/zirconia nanolaminates are fabricated. Lateral downscaling the devices below 10 µm2 enables 20 ns programming with electrical pulses, dissipating ≤ 3 pJ. Experimental results show that final conductance state is set by pulse amplitude, and is largely independent of the initial ...
Alexandre Baigol +7 more
wiley +1 more source
How episodic and working memory affect rule- and memory-based judgments [PDF]
, 2013 Making accurate judgments is an essential skill in everyday life. However, little is known about the basic cognitive skills required for accurate judgments. Research on judgment and categorization processes suggests that people rely on various strategies
Rieskamp, Jörg +4 more
core +1 more source
Chronic Disease Monitoring Using Advanced Compliant Materials for Bioelectronics
Advanced Electronic Materials, EarlyView.Compliant bioelectronic systems enable continuous monitoring of chronic disease through soft, stretchable materials and tissue‐conformal designs that support stable electrophysiological, mechanical, and biochemical sensing. Integration of diverse sensing modalities with thoughtful material selection, device architectures, and advanced fabrication ...
Han Kim +7 more
wiley +1 more source
Understanding Egg Price Volatility and Policy Implications in the U.S. With Machine Learning
Applied Economic Perspectives and Policy, EarlyView.ABSTRACT Eggs are an inexpensive and sustainable source of proteins, but volatility in the U.S. egg prices has intensified in recent years, raising concerns over food affordability and market stability. This study examines the drivers of U.S. egg price dynamics over 2004–2025 using a two‐stage framework that combines LASSO‐based variable selection with
Xuemei Zhao +3 more
wiley +1 more source
Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook
Advanced Intelligent Discovery, EarlyView.Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang +4 more
wiley +1 more source
Frontiers in PharmacologySlow wave sleep (SWS) is highly relevant for verbal and non-verbal/spatial memory in healthy individuals, but also in people with epilepsy. However, contradictory findings exist regarding the effect of seizures on overnight memory retention, particularly
Yvonne Höller +3 more
doaj +1 more source