Transform Windows 11's virtual SDR-in-HDR curve from piecewise sRGB to Gamma 2.2

PeRFlow: Piecewise Rectified Flow as Universal Plug-and-Play Accelerator (NeurIPS 2024)

fit piecewise linear data for a specified number of line segments

A Piecewise-Pinhole Monocular Fisheye SLAM System

DPPTAM: Dense Piecewise Planar Tracking and Mapping from a Monocular Sequence

A curated list on piecewise-planar reconstruction

An implementation of piecewise linear time warping for multi-dimensional time series alignment

Piecewise Structural Equation Modeling in R

Python library for piecewise linear interpolation in multiple dimensions with multiple, arbitrarily placed, masters.

piecewise-regression (aka segmented regression) in python. For fitting straight line models to data with one or more breakpoints where the gradient changes.

Unsupervised multilabel image segmentation (color/gray/multichannel) based on the Potts model (aka piecewise constant Mumford-Shah model)

## Auto-archived due to inactivity. ## Functions for piecewise regression on time series data

Secured Constraints Unit Commitment model of Power system, including the model based on AC flow equation and DC flow equation. Only the constraints in pre-contingency state are considered. There is a piecewise function expression for power generation costs. However, I'm sorry that the version is relative old, and it may be difficult to read or modify. 电力系统安全约束单位承诺模型，包括基于交流潮流方程和直流潮流方程的模型。 仅考虑意外前状态下的约束。 有一个用于发电成本的分段函数表达式。 但是，很抱歉该版本相对较旧，可能难以阅读或修改。 Besides, note that the model is based on the Matlab, Yalmip, and the solver is Gurobi. It can be changed to other solvers, such as Cplex, by modifying the parameter 'gurobi' in sentence 'ops = settings('solver','gurobi''. 此外，请注意，该模型基于Matlab，Yalmip，求解器为Gurobi。 通过修改句子'ops = settings('solver'，'gurobi'中的参数'gurobi'，可以将其更改为其他求解器，例如Cplex。 If you have any idea on improving this model, please contact me. 如果您有任何改进此模型的想法，请联系我

Sleek implementations of the ZigZag, Boomerang and other assorted piecewise deterministic Markov processes for Markov Chain Monte Carlo including Sticky PDMPs for variable selection

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Piecewise linear representation of 1D data in Python

[CVPR'21] Locally Aware Piecewise Transformation Fields for 3D Human Mesh Registration

Piecewise Rigid Scene Model - Implementation IJCV'15

Lightweight, High-Performance and easy-to-use library for performing Affine, Projective or Piecewise Affine transformations over any Image or HTMLElement from only a set of reference points. In Javascript.

[ISPRS 2025] Piecewise-ICP: Efficient and Robust Registration for 4D Point Clouds in Permanent Laser Scanning

Code for our paper at ECCV 2020: Post-Training Piecewise Linear Quantization for Deep Neural Networks

Real-Time Minimization of the Piecewise Smooth Mumford-Shah Functional

Solve optimization problems containing piecewise linear functions

Piecewise Linear Functions (PWL) implementation in PyTorch

Python function to interpolate GPX data using piecewise cubic Hermite splines

FastCap is the premium capacitance solver originally developed at M.I.T. on Unix platform. A de-facto golden reference standard, FastCap extracts the capacitances of any 3D conductive geometry in free space or embedded in arbitrary, piecewise-constant dielectrics, by solving the Maxwell equations in quasi-static regime. For more information, visit our website.

Piecewise alignment for layers of mosaics

n-dimensional piecewise linear interpolation using Delaunay triangulation in C++

High order and sparse layers in pytorch. Lagrange Polynomial, Piecewise Lagrange Polynomial, Piecewise Discontinuous Lagrange Polynomial (Chebyshev nodes) and Fourier Series layers of arbitrary order. Piecewise implementations could be thought of as a 1d grid (for each neuron) where each grid element is Lagrange polynomial. Both full connected and convolutional layers included.

Probabilistic state estimation for robotics applications. Bayes filters include Kalman, Markov chains; Gaussian, uniform and discrete mapping probability distributions representations; Distribution sampling, marginalization, multiplication; Distribution composition independent pairs and Bayes rule; Linear algebra, matrix, vector, inverse, square root, LU decomposition, Cholesky decomposition; piecewise linear approximation of functions; Sensor models, Markov action chains <X,U,X>.