Results 111 to 120 of about 1,596 (244)

Hardware acceleration of number theoretic transform for zk‐SNARK

Engineering Reports, EarlyView., 2023
An FPGA‐based hardware accelerator with a multi‐level pipeline is designed to support the large‐bitwidth and large‐scale NTT tasks in zk‐SNARK. It can be flexibly scaled to different scales of FPGAs and has been equipped in the heterogeneous acceleration system with the help of HLS and OpenCL.
Haixu Zhao, Dong Ding, Feng Wang, Pengcheng Hua, Ning Wang, Qin Wu, Zhilei Chai   +6 more
wiley   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source

Investigating 2-iterated degenerate 2D Appell polynomials and their diverse applications

This research delves into the realm of special polynomials, emphasizing the integration of the monomiality principle alongside operational rules and related properties.
Wani, Shahid Ahmad, Lande, Chhaya, Fuentes Gandara, Fabio Armando, Khan, Waseem Ahmad   +3 more
core   +1 more source

A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws

Advanced Intelligent Discovery, EarlyView.
The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows, G. Zhang, S. Anand, Z. Chen, J. Lin, A. Desai, S. Martiniani, F. Caravelli   +7 more
wiley   +1 more source

Hankel determinants of certain sequences of Bernoulli polynomials: A direct proof of an inverse matrix entry from statistics

We calculate the Hankel determinants of sequences of Bernoulli polynomials. This corresponding Hankel matrix comes from statistically estimating the variance in nonparametric regression.
Li, Ye, Jiu, Lin
core   +2 more sources

Gaussian Process Regression–Neural Network Hybrid with Optimized Redundant Coordinates: A New Simple Yet Potent Tool for Scientist's Machine Learning Toolbox

Advanced Intelligent Discovery, EarlyView.
A machine learning method, opt‐GPRNN, is presented that combines the advantages of neural networks and kernel regressions. It is based on additive GPR in optimized redundant coordinates and allows building a representation of the target with a small number of terms while avoiding overfitting when the number of terms is larger than optimal.
Sergei Manzhos, Manabu Ihara
wiley   +1 more source

Interpretability and Representability of Commutative Algebra, Algebraic Topology, and Topological Spectral Theory for Real‐World Data

Advanced Intelligent Discovery, EarlyView.
This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley   +1 more source

Differential Equation of Appell Polynomials Via the Factorization Method

, 2002
Let {Pn(x)}∞n=0 be a sequence of polynomials of degree n. We define two sequences of differential operators Φn and Ψn satisfying the following properties: By constructing these two operators for Appell polynomials, we determine their differential ...
He, Matthew, Ricci, P.E., Ricci, Paolo E., He, M.X.   +3 more
core   +1 more source

Composition‐Aware Cross‐Sectional Integration for Spatial Transcriptomics

Advanced Intelligent Discovery, EarlyView.
Multi‐section spatial transcriptomics demands coherent cell‐type deconvolution, domain detection, and batch correction, yet existing pipelines treat these tasks separately. FUSION unifies them within a composition‐aware latent framework, modeling reads as cell‐type–specific topics and clustering in embedding space.
Qishi Dong, Zijian Huang, Xuanwu Wang, Zhenghui Feng, Wei Liu, Bingding Huang   +5 more
wiley   +1 more source

Sequences of twice-iterated Δw-Gould–Hopper Appell polynomials

In this paper, we introduce general sequence of twice-iterated (Formula presented.) -(degenerate) Gould–Hopper Appell polynomials (TI-DGHAP) via discrete (Formula presented.) -Gould–Hopper Appell convolution.
ÇEKİM, BAYRAM, Biricik, NESLİHAN, Özarslan, Mehmet Ali   +2 more
core   +1 more source