Related papers: PIETOOLS 2025: User Manual
pdepath 2.0 is an upgrade of the continuation/bifurcation package pde2path for elliptic systems of PDEs over bounded 2D domains, based on the Matlab pdetoolbox. The new features include a more efficient use of FEM, easier switching between…
A template-based generic programming approach was presented in a previous paper that separates the development effort of programming a physical model from that of computing additional quantities, such as derivatives, needed for embedded…
This document summarizes the main concepts of the finite element (FE) theory and constitutive relations as implemented in the open-source code phase-field multiphysics materials simulator PHIMATS https://github.com/ahcomat/PHIMATS. PHIMATS…
SModelS is an automatised tool for the interpretation of simplified model results from the LHC. It allows to decompose models of new physics obeying a Z2 symmetry into simplified model components, and to compare these against a large…
PyODDS is an end-to end Python system for outlier detection with database support. PyODDS provides outlier detection algorithms which meet the demands for users in different fields, w/wo data science or machine learning background. PyODDS…
AutoML systems targeting novices often prioritize algorithmic automation over usability, leaving gaps in users' understanding, trust, and end-to-end workflow support. To address these issues, we propose an abstract pipeline that covers data…
Many real-world optimization problems exhibit dynamic characteristics, posing significant challenges for traditional optimization techniques. Evolutionary Dynamic Optimization Algorithms (EDOAs) are designed to address these challenges…
PiML (read $\pi$-ML, /`pai`em`el/) is an integrated and open-access Python toolbox for interpretable machine learning model development and model diagnostics. It is designed with machine learning workflows in both low-code and high-code…
Partial Differential Equations (PDEs) have long been recognized as powerful tools for image processing and analysis, providing a framework to model and exploit structural and geometric properties inherent in visual data. Over the years,…
Delay-Differential Equations (DDEs) are the most common representation for systems with delay. However, the DDE representation is limited. In network models with delay, the delayed channels are low-dimensional and accounting for this…
This technical report introduces PaddleOCR 3.0, an Apache-licensed open-source toolkit for OCR and document parsing. To address the growing demand for document understanding in the era of large language models, PaddleOCR 3.0 presents three…
With the development of widely available commercial eye trackers, the use of eye tracking and pupillometry have become prevalent tools in cognitive research, both in industry and academia. However, dealing with pupil recordings often proves…
In practical applications of machine learning, it is necessary to look beyond standard metrics such as test accuracy in order to validate various qualitative properties of a model. Partial dependence plots (PDP), including instance-specific…
This article introduces a general purpose framework and software to approximate partial differential equations (PDEs). The sparsity patterns of finite element discretized operators is identified automatically using the tools from…
PINGSoft, is a set of IDL routines designed to visualise, manipulate, and analyse integral field spectroscopy (IFS) data regardless of the original instrument and spaxel shape. PINGSoft 2 is a relatively major upgrade with respect to the…
The formulae relevant for the Linear Optics design of Synchrotrons are derived systematically from first principles, a straightforward exercise in Hamiltonian Dynamics. Equipped with these, the relevant "Use Cases" are then captured for a…
Physics-informed machine learning (PIML) integrates partial differential equations (PDEs) into machine learning models to solve inverse problems, such as estimating coefficient functions (e.g., the Hamiltonian function) that characterize…
MLOps tools enable continuous development of machine learning, following the DevOps process. Different MLOps tools have been presented on the market, however, such a number of tools often create confusion on the most appropriate tool to be…
Developing Piping and Instrumentation Diagrams (P&IDs) is a crucial step during the development of chemical processes. Currently, this is a tedious, manual, and time-consuming task. We propose a novel, completely data-driven method for the…
This manual describes a set of utilities developed for Lattice QCD computations. They are collectively called QCDUtils. They comprise a set of Python programs each of them with a specific function: download gauge ensembles from the public…