#Kalman-filter
Showing 29 of 29 repositories tagged #kalman-filter, ranked by stars
Collection of notebooks about quantitative finance, with interactive python code.
Udacity Self-Driving Car Engineer Nanodegree projects.
A library for differentiable robotics on manifolds.
A Python package for probabilistic state space modeling with JAX
Kalman filter library
[NeurIPS Workshop 2019] Official code of the paper "Probabilistic 3D Multi-Object Tracking for Autonomous Driving." First Place of the First NuScenes Tracking Challenge in the AI Driving Olympics Workshop of NeurIPS.
A stock backtesting engine written in Java. And a pairs trading (cointegration) strategy implementation using a bayesian kalman filter model
RoboMaster 视觉自瞄，包含陀螺运动建模 lmtd、精密火控 watergun、弹道校正 aim-corrector 和各种视觉基础组件
Book and material for the course "Time series analysis with Python" (STA-2003)
C++ implementation of BoT-SORT MOT algorithm with Re-ID and Camera Motion Compensation
Repository for Eye Gaze Detection and Tracking
Automated, smooth, N'th order derivatives of non-uniformly sampled time series data
Codera Quant is a Java framework for algorithmic trading strategies development, execution and backtesting via Interactive Brokers TWS API or other brokers API
Visualizations of algorithms covered in Sebastian Thrun's excellent Artificial Intelligence for Robotics course on Udacity.
R code for Time Series Analysis and Its Applications, Ed 4
Kalman Variational Auto-Encoder
R package to accompany Time Series Analysis and Its Applications: With R Examples -and- Time Series: A Data Analysis Approach Using R
Multi-Modal Sensor Fusion and Object Tracking for Autonomous Racing
Kalman filter implementation in Rust
A demo showing the pose of the mpu6050 in 3D using esp-idf
Neural-Kalman GNSS/INS Navigation for Precision Agriculture
Using Kalman Filter to Predict Corona Virus Spread
An extended Kalman Filter implementation in Python for fusing lidar and radar sensor measurements
Udacity Self Driving Car ND projects - including lane detection, Traffic sign classifier, behaviour cloning
Recursive Leasting Squares (RLS) with Neural Network for fast learning
High Frequency Trading strategies.
Implementation of Kalmanformer, modeling the Kalman gain with a transformer
Python library to implement advanced trading strategies using machine learning and perform backtesting.
Built a pairs trading strategy in emerging markets using a rolling Kalman-filter beta and spread half-life, with z-score position sizing, and comprehensive back-testing with liquidity adjustments and transaction cost analysis for enhanced risk management