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passion4energy's Projects

pypsa icon pypsa

PyPSA: Python for Power System Analysis

pyro icon pyro

Deep universal probabilistic programming with Python and PyTorch

pysb icon pysb

Python framework for Systems Biology modeling

pysindy icon pysindy

A package for the sparse identification of nonlinear dynamical systems from data

pyslam icon pyslam

Non-linear least-squares SLAM in Python using scipy and numpy. Modelled after Google's Ceres solver.

pysmooth icon pysmooth

A unique time series library in Python that consists of Kalman filters (discrete, extended, and unscented), online ARIMA, and time difference model.

pyswarm icon pyswarm

Particle swarm optimization (PSO) that supports constraints

python-control icon python-control

The Python Control Systems Library is a Python module that implements basic operations for analysis and design of feedback control systems.

python-mip icon python-mip

Collection of Python tools for the modeling and solution of Mixed-Integer Linear programs

python-mle icon python-mle

A Python package for performing Maximum Likelihood Estimates

pytorch icon pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

pytorchtimeseries icon pytorchtimeseries

This repository demonstrates how to implement tap-delays (TDL) in PyTorch framework for time series modeling. Currently, NARX and NARMAX have been implemented.

pyts icon pyts

A Python package for time series classification

pytutorials icon pytutorials

A collection of tutorials for the Python programming language, especially for control theoretic purposes.

pywr icon pywr

Pywr is a generalised network resource allocation model written in Python.

qpth icon qpth

A fast and differentiable QP solver for PyTorch.

quadpy icon quadpy

:triangular_ruler: Numerical integration (quadrature, cubature) in Python

quantecon.py icon quantecon.py

A community based Python library for quantitative economics

quantpy icon quantpy

A framework for quantitative finance In python.

raindrop icon raindrop

Raindrop strategy for Irregular time series

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