Results 191 to 200 of about 1,302,044 (285)
A Flexible and Energy‐Efficient Compute‐in‐Memory Accelerator for Kolmogorov–Arnold Networks
This article presents KA‐CIM, a compute‐in‐memory accelerator for Kolmogorov–Arnold Networks (KANs). It enables flexible and efficient computation of arbitrary nonlinear functions through cross‐layer co‐optimization from algorithm to device. KA‐CIM surpasses CPU, ASIC, VMM‐CIM, and prior KAN accelerators by 1–3 orders of magnitude in energy‐delay ...
Chirag Sudarshan +6 more
wiley +1 more source
Detecting Polarized Side-Scattering Signals in Media with Ultra-Low-Scattering Coefficients: An Improved Monte Carlo Simulation Approach. [PDF]
Shan C, He L, Jin B, Wu Z, Yi S.
europepmc +1 more source
Explainable artificial intelligence (XAI) guides selective electrode activation in retinal prostheses by emphasizing visually informative regions. XAI‐assisted phosphene generation maintains object recognition performance while significantly reducing stimulation power.
Sein Kim, Hamin Shim, Maesoon Im
wiley +1 more source
A Monte Carlo study of proton LET calculations: Comparison between the codes PENHAN, FLUKA, and TOPAS. [PDF]
Puerta D, Anguiano M, González W.
europepmc +1 more source
Artificial intelligence (AI) is reshaping autonomous mobile robot navigation beyond classical pipelines. This review analyzes how AI techniques are integrated into core navigation tasks, including path planning and control, localization and mapping, perception, and context‐aware decision‐making. Learning‐based, probabilistic, and soft‐computing methods
Giovanna Guaragnella +5 more
wiley +1 more source
High-density lead-free alloys for compact and sustainable photon shielding: a Monte Carlo and benchmarking study. [PDF]
Hamad MK.
europepmc +1 more source
A memory‐assisted dynamic‐latch ADC integrating charge‐trap flash enables ultra‐low‐energy quantization and in‐ADC nonlinear activation for variation‐tolerant neuromorphic computing. Analog‐to‐digital converters (ADCs) remain the dominant area/energy bottleneck in neuromorphic computing (NC) systems.
Jonghyun Ko +4 more
wiley +1 more source
Impact of extraction methods on Monte Carlo based dietary health risk assessment of potentially harmful elements in edible plants. [PDF]
Stolecka A, Gruszecka-Kosowska A.
europepmc +1 more source
Physics‐Informed Neural Networks (PINNs) provide a framework for integrating physical laws with data. However, their application to Prognostics and Health Management (PHM) remains constrained by the limited uncertainty quantification (UQ) capabilities.
Ibai Ramirez +4 more
wiley +1 more source
Threshold-Filtered Kinetic Monte Carlo Simulation for Real-Time Simulation and Control of Biomass Fractionation. [PDF]
Kim J, Ryu J, Yang Q, Yoo CG, Kwon JS.
europepmc +1 more source

