Results 161 to 170 of about 12,571,794 (304)

LLM‐Assisted Design of Ultralow‐κ$\kappa$ Chalcogenides

Advanced Science, EarlyView.
An AI assisted, physics guided workflow accelerates the discovery of ultralow thermal conductivity materials by combining Bayesian optimization, evidence conditioned LLM reasoning, and automated physics‐based validation. The framework uncovers dynamically stable Ag based chalcogenides with ultralow thermal conductivity and promising thermoelectric ...
Yujie Liu, Congran Jia, Yuzhou Hao, Xuejie Li, Yang Wang, Artem Oganov, Jun Sun, Xiangdong Ding, Turab Lookman, Zhibin Gao   +9 more
wiley   +1 more source

Bayesian Adaptive Hamiltonian Monte Carlo with an Application to High-Dimensional BEKK GARCH Models [PDF]

Hamiltonian Monte Carlo (HMC) is a recent statistical procedure to sample from complex distributions. Distant proposal draws are taken in a equence of steps following the Hamiltonian dynamics of the underlying parameter space, often yielding superior ...
John Maheu, Martin Burda
core   +2 more sources

Applying Monte Carlo Method for Straight-Line Model Sensor Calibration. [PDF]

Sensors (Basel)
Ramos PM, Janeiro FM.
europepmc   +1 more source

Numerical Study of Gas Flow in Super Nanoporous Materials Using the Direct Simulation Monte-Carlo Method. [PDF]

Micromachines (Basel), 2023
Shariati V, Roohi E, Ebrahimi A.
europepmc   +1 more source

Hardware‐Native Gaussian Sampling With Probabilistic Ising Machines for Modern Communication Paradigms

Advanced Science, EarlyView.
Probabilistic Ising machines are introduced as hardware‐native Gaussian samplers for edge communication workloads. Tunable variance and sampling density enable accurate distributions for Falcon‐class post‐quantum signatures and diffusion‐based semantic communication.
Davi Rodrigues, Andrea Grimaldi, Deborah Volpe, Youwei Bao, Shuhan Yang, Eleonora Grassucci, Giulio Siracusano, Massimo Chiappini, Mario Carpentieri, Hyunsoo Yang, Giovanni Finocchio   +10 more
wiley   +1 more source

A Quasi-Monte Carlo Method Based on Neural Autoregressive Flow. [PDF]

Entropy (Basel)
Wei Y, Xi W.
europepmc   +1 more source

Gap-filling of ocean color over the tropical Indian Ocean using Monte-Carlo method. [PDF]

Sci Rep, 2022
Modi A, Roxy MK, Ghosh S.
europepmc   +1 more source

CeO2‐Based Electrocatalysts for the Oxygen Evolution Reaction: Design, Dynamic Mechanisms, and Electrolyte Adaptability

Advanced Science, EarlyView.
This Review shows how cerium oxide helps water‐splitting catalysts work better and last longer. It explains how CeO2 tunes electronic structure, oxygen‐vacancy behavior, and surface reconstruction, while adapting to alkaline, acidic, and seawater conditions.
Zhen Cui, Ailing Song, Zirui Cui, Manman Duanmu, Zhipeng Ma, Hao Liu, Guangjie Shao, Xinyi Tan, Guoxiu Wang, Hao Tian   +9 more
wiley   +1 more source

Zero variance in Markov chain Monte Carlo with an application to credit risk estimation [PDF]

We propose a general purpose variance reduction technique for Markov Chain Monte Carlo estimators based on the Zero-Variance principle introduced in the physics lit- erature by Assaraf and Caarel ( 1999). The potential of the new idea is illustrated with
Tenconi Paolo
core  

Evaluation of radiation damage effects of low-energy Auger and conversion electrons emitted by ¹³⁴Ce decay using a Monte Carlo method. [PDF]

Sci Rep
Lee S, Kim W, Kim D, Shin J, Huh Y, Bobba KN, Flavell RR, Cho G, Seo Y.   +8 more
europepmc   +1 more source