Results 151 to 160 of about 3,984,242 (310)

Discrete Mathematics, Probability Theory and Stochastic Processes [PDF]

Samir Brahim Belhaouari, Halima Bensmail, Farshid Mehrdoust   +2 more
openalex   +1 more source

Probabilistic Thinking Level of Junior High School Students with Low Mathematical Abilities Who Have Not Learn Probability Material

, 2021
Siti Khoirunnisa, İmam Sujadi, Sri Subanti   +2 more
openalex   +2 more sources

Exploring Quantum Support Vector Regression for Predicting Hydrogen Storage Capacity of Nanoporous Materials

Advanced Intelligent Discovery, EarlyView.
In this study we employed support vector regressor and quantum support vector regressor to predict the hydrogen storage capacity of metal–organic frameworks using structural and physicochemical descriptors. This study presents a comparative analysis of classical support vector regression (SVR) and quantum support vector regression (QSVR) in predicting ...
Chandra Chowdhury
wiley   +1 more source

A multi-season epidemic model with random genetic drift and transmissibility. [PDF]

J Math Biol
Britton T, Pugliese A.
europepmc   +1 more source

A Brief Discussion on the Connection Between Secondary School Mathematics and University Mathematics from a Higher Perspective: Taking Probability Theory as an Example [PDF]

Zilan Xu
openalex   +1 more source

Wiley Series in Probability and Mathematics Statistics

, 2005
P. J. Huber
semanticscholar   +1 more source

Designing Memristive Materials for Artificial Dynamic Intelligence

Advanced Intelligent Discovery, EarlyView.
Key characteristics required of memristors for realizing next‐generation computing, along with modeling approaches employed to analyze their underlying mechanisms. These modeling techniques span from the atomic scale to the array scale and cover temporal scales ranging from picoseconds to microseconds. Hardware architectures inspired by neural networks
Youngmin Kim, Ho Won Jang
wiley   +1 more source

Controlled bidirectional teleportation of unknown single-particle states by using an arbitrary high-dimensional entangled state. [PDF]

PLoS One
Lei H, Tang J, Peng J.
europepmc   +1 more source

The Nature of Misconceptions and Cognitive Obstacles Faced by Secondary School Mathematics Students in Understanding Probability: A Case Study of Selected Polokwane Secondary Schools

, 2014
Paul Mutodi, Hlanganipai Ngirande
openalex   +2 more sources

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source