Quanta Magazine

Networks Hold the Key to a Decades-Old Problem About Waves

Mathematicians are still trying to understand fundamental properties of the Fourier transform, one of their most ubiquitous ...
EurekAlert!

Multivariate basic function secret sharing from oblivious transfer

Function secret sharing (FSS) is a secret sharing technique for functions in a specific function class, mainly including distributed point function (DPF) and distributed comparison function (DCF). As ...
Scientific Research Publishing

Leshno, M., Lin, V.Y., Pinkus, A. and Schocken, S. (1993) Multilayer Feedforward Networks with a Nonpolynomial Activation Function Can Approximate Any Function. Neural Networks ...

ABSTRACT: We explore the performance of various artificial neural network architectures, including a multilayer perceptron (MLP), Kolmogorov-Arnold network (KAN), LSTM-GRU hybrid recursive neural ...
GitHub

Multivariable: Space and Functions

Learn to choose coordinate systems, visualize multivariable functions, and parameterize curves. You can use these live scripts as demonstrations in lectures, class activities, or interactive ...
GitHub

Root-finding methods for both univariate, scalar-valued functions and multivariate, vector-valued functions.

Please see https://docs.rs/rootfinder. Licensed under either of Apache License, Version 2.0 or MIT license at your option. Unless you explicitly state otherwise, any ...
Frontiers

A Boolean sum interpolation for multivariate functions of bounded variation

1 Institute of Mathematics, University of Lübeck, Lübeck, Germany 2 Institute of Mathematics, National Academy of Sciences of Ukraine, Kyiv, Ukraine This paper ...
Quanta Magazine

Novel Architecture Makes Neural Networks More Understandable

“Neural networks are currently the most powerful tools in artificial intelligence,” said Sebastian Wetzel, a researcher at the Perimeter Institute for Theoretical Physics. “When we scale them up to ...
IEEE

Correlation-Aware Spatial–Temporal Graph Learning for Multivariate Time-Series Anomaly Detection

Abstract: Multivariate time-series anomaly detection is critically important in many applications, including retail, transportation, power grid, and water treatment plants. Existing approaches for ...
IEEE

Inverse of multivariable linear time varying bond-graph models

Abstract: In this paper, we propose to study the inversion of multivariable linear time varying systems modelled by bond-graph approach. Thus, an analysis method based on non-commutative differential ...
Frontiers

A brain functional network feature extraction method based on directed transfer function and graph theory for MI-BCI decoding tasks

Background: The development of Brain-Computer Interface (BCI) technology has brought tremendous potential to various fields. In recent years, prominent research has focused on enhancing the accuracy ...