BIOENGINEER

Python Library Analyzes Spatial Feature Distributions in Laser Breakdown Spectroscopy Imaging

Researchers have developed pylibs-stats, an open-source Python library that analyzes per-pixel feature distributions in laser ...
BIOENGINEER

Symbolic Regression Automates Particle Physics Background Modeling With Single-Run Uncertainty Estimates

Researchers developed SymbolFit, a symbolic regression framework that automates parametric function discovery and uncertainty ...
marktechpost

NVIDIA Releases Kumo Tabular: Open Tabular Foundation Models That Predict New Rows in a Single Forward Pass

NVIDIA has released Kumo Tabular, a new family of tabular foundation models (TFMs) for classification and regression. If you have followed TabPFN or TabICL, the setup will look familiar. The model ...
blog.csdn

核函数是GPR的灵魂：Gaussian-Process-Regression-Tutorial详解RBF平方指数核如何让随机函数变平滑

核函数是GPR的灵魂：Gaussian-Process-Regression-Tutorial详解RBF平方指数核如何让随机函数变平滑 【免费下载链接】Gaussian-Process-Regression-Tutorial An Intuitive Tutorial to Gaussian Processes Regression 项目地址: https ...
POWER Magazine

Fives ProSim Launches ProSimPlus Python API, a New Generation of Python Driven Process Simulation

Fives ProSim, a subsidiary of the Fives Group and an expert in industrial process simulation and optimization, announces the release of ProSimPlus Python API. This new solution enables users to run ...
Forbes

People, Process, Technology And The Shift Nobody Saw Coming

Forbes contributors publish independent expert analyses and insights. Robert, founder of KramerERP, covers AI, ERP, SCM, data and security. This voice experience is generated by AI. Learn more. This ...
IEEE

Efficient and Scalable Tobit Gaussian Process Regression for Modeling Air Quality Data

Abstract: Tobit Gaussian process regression (T-GPR) model extends the classical Tobit regression model by incorporating the flexibility of Gaussian processes, thereby enabling the characterization of ...
IEEE

Incremental Heteroscedastic Gaussian Process Regression and Its Applications in Model Predictive Control

Abstract: Gaussian process regression (GPR) models are becoming increasingly tightly integrated into robotic systems, particularly in the context of robot model predictive control (MPC) operating in ...
blog.csdn

Gaussian-Process-Regression-Tutorial：高斯过程回归入门教程

Gaussian-Process-Regression-Tutorial 是一个面向希望使用高斯过程（Gaussian Process, GP）进行回归但又不熟悉其理论基础的初学者设计的教程。该项目以直观易懂的方式，从基础数学概念讲起，逐步深入 ...
Scientific Research Publishing

Rasmussen, C.E. and Williams, C.K.I. (2005) Gaussian Processes for Machine Learning. The MIT Press.

ABSTRACT: This paper introduces a method to develop a common model based on machine learning (ML) that predicts the mechanical behavior of a family with three composite materials. The latter are ...