A Bayesian model selection approach for identifying differentially expressed transcripts from RNA sequencing data. [PDF]
J R Stat Soc Ser C Appl Stat, 2018 Papastamoulis P, Rattray M.
europepmc +1 more source
Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference
Advanced Electronic Materials, EarlyView.This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho +6 more
wiley +1 more source
Stochastic‐MTJ Sampler Arrays for In‐Array Monte–Carlo Estimation
Advanced Electronic Materials, EarlyView.A low‐energy‐barrier magnetic tunnel junction array is operated as a probability‐domain sampler: each cell's random switching, programmed through a shared digital‐to‐analog converter, makes the per‐column multiply–accumulate an unbiased Monte–Carlo expectation estimator that returns both a mean and a calibrated uncertainty.
Ran Zhang +6 more
wiley +1 more source
Topologically-based parameter inference for agent-based model selection from spatiotemporal cellular data. [PDF]
PLoS Comput BiolWenzel AR +5 more
europepmc +1 more source
Advanced Electronic Materials, EarlyView.A compact QASRR‐based THz metamaterial absorber enables polarization‐insensitive dual‐band absorption and skin‐cancer‐related refractive‐index sensing through measurable resonance shifts. Field, surface‐current, and circuit analyses clarify the dual‐resonance mechanism, while StackNet‐assisted prediction accurately estimates the simulated absorption ...
Md. Murad Kabir Nipun +5 more
wiley +1 more source
Artificial Intelligence for Fluorite Ferroelectric Materials: From Discovery to Optimization
Advanced Electronic Materials, EarlyView.Artificial intelligence accelerates the discovery and optimization of HfO2‐based fluorite ferroelectrics by linking synthesis, structure, properties, and device performance. Machine learning, deep‐learning analysis, and AI‐driven atomistic modeling enable predictive design, dopant screening, and closed‐loop optimization toward next‐generation ...
Faizan Ali +3 more
wiley +1 more source
Dynamic image-informed selection of biomechanical tumor growth models. [PDF]
Biomech Model MechanobiolNoman AA +3 more
europepmc +1 more source
A Dual‐Branch Flux‐Based Extended Memristor Model With Machine‐Learning‐Assisted Calibration
Advanced Electronic Materials, EarlyView.Multilayer oxide memristors integrated in crossbar arrays are described through a dual‐branch, flux‐controlled compact model. A three‐stage calibration workflow combining Latin hypercube sampling, Bayesian optimization, and gradient‐based refinement extracts device parameters from experimental data.
Davide Rossetti +6 more
wiley +1 more source
A Comparison of Item Selection Methods and Parameter Estimation Approaches for Online Calibration in Computerized Adaptive Testing. [PDF]
Educ Psychol MeasErtuna L, Glas CAW, Atar B.
europepmc +1 more source
Advanced Electronic Materials, EarlyView.Compositionally engineered hafnium–zirconium oxide capacitors are described by an extended Landau–Khalatnikov framework incorporating inertial and nonlinear damping terms. The unified model captures ferroelectric and volatile regimes within a single material platform, linking free‐energy landscapes to circuit‐level behavior.
Davide Rossetti +15 more
wiley +1 more source