Results 111 to 120 of about 129,225 (287)
A genetic-algorithms based evolutionary computational neural network for modelling spatial interaction data [PDF]
Building a feedforward computational neural network model (CNN) involves two distinct tasks: determination of the network topology and weight estimation.
Manfred M. Fischer, Yee Leung
core
Device‐Level Implementation of Reservoir Computing With Memristors
Reservoir computing (RC) is an emerging computing scheme that employs a reservoir and a single readout layer, which can be actualized in the nanoscale with memristors. As a comprehensive overview, the principles of RC and the switching mechanisms of memristors are discussed, followed by actual demonstrations of memristor‐based RC and the remaining ...
Sunbeom Park, Hyojung Kim, Ho Won Jang
wiley +1 more source
Spike-based computation using classical recurrent neural networks
Spiking neural networks (SNNs) are a type of artificial neural networks in which communication between neurons is only made of events, also called spikes.
Florent De Geeter +2 more
doaj +1 more source
Droplet‐based microfluidics enables precise, high‐throughput microscale reactions but continues to face challenges in scalability, reproducibility, and data complexity. This review examines how artificial intelligence enhances droplet generation, detection, sorting, and adaptive control and discusses emerging opportunities for clinical and industrial ...
Junyan Lai +10 more
wiley +1 more source
This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy +2 more
wiley +1 more source
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal +6 more
wiley +1 more source
Equilibrium Propagation for Dissipative Dynamics
This work develops local learning rules for damped linear dynamical systems, including mechanical structures and resistor‐inductor‐capacitor (RLC) circuits, by leveraging an effective action formulation. It demonstrates how physical systems can autonomously compute gradients and learn temporal patterns, enabling applications such as sound ...
Marc Berneman, Daniel Hexner
wiley +1 more source
Material‐Based Intelligence: Autonomous Adaptation and Embodied Computation in Physical Substrates
This perspective formulates a unifying framework for Material‐Based Intelligence (MBI), defining the physical requirements for materials to achieve embodied action, active memory and embodied information processing through intrinsic nonequilibrium dynamics. The design of intelligent materials often draws parallels with the complex adaptive behaviors of
Vladimir A. Baulin +4 more
wiley +1 more source

