Krozard

Krozard's Stars

• pymc-devs/pymc

  Bayesian Modeling and Probabilistic Programming in Python

  Language:Python8.7k2243.3k2k

• jmschrei/pomegranate

  Fast, flexible and easy to use probabilistic modelling in Python.

  Language:Python3.4k95782590

• hmmlearn/hmmlearn

  Hidden Markov Models in Python, with scikit-learn like API

  Language:Python3.1k121440739

• markdregan/Bayesian-Modelling-in-Python

  A python tutorial on bayesian modeling techniques (PyMC3)

  Language:Jupyter Notebook2.5k1617414

• abhineet123/Deep-Learning-for-Tracking-and-Detection

  Collection of papers, datasets, code and other resources for object tracking and detection using deep learning

  Language:HTML2.4k1566656

• MouseLand/cellpose

  a generalist algorithm for cellular segmentation with human-in-the-loop capabilities

  Language:Jupyter Notebook1.4k29881393

• aloctavodia/Doing_bayesian_data_analysis

  Python/PyMC3 versions of the programs described in Doing bayesian data analysis by John K. Kruschke

  Language:Jupyter Notebook893674284

• shuyo/iir

  Machine Learning / Natural Language Processing / Information Retrieval

  Language:Python7095917297

• mattjj/pyhsmm

  Language:Python5485699174

• hyseob/MDNet

  Learning Multi-Domain Convolutional Neural Networks for Visual Tracking

  Language:C++4704721177

• fonnesbeck/scipy2014_tutorial

  Tutorial: Bayesian Statistical Analysis in Python

  Language:Jupyter Notebook316274167

• bnpy/bnpy

  Bayesian nonparametric machine learning for Python

  Language:Python210193858

• mattjj/pybasicbayes

  Language:Python153202760

• pondruska/DeepTracking

  Source code of DeepTracking research project

  Language:Lua12923649

• hstrey/Hidden-Markov-Models-pymc3

  Implementation of Hidden Markov Models in pymc3

  Language:Jupyter Notebook592121

• duducheng/Learning-Notes

  Notes and resources on Machine Learning

  5513016

• AnDiChallenge/andi_datasets

  andi_datasets provides functions to generate, save, load and manipulate datasets of diffusion anomalous trajectories. It is part of the Anomalous Diffusion (ANDI) Challenge.

  Language:Jupyter Notebook264814

• HEPTrkX/heptrkx-ctd

  heptrkx-ctd

  Language:Jupyter Notebook18609

• yoyohoho0221/pt_linking

  This is the repository for paper "Deep learning method for data association in particle tracking"

  Language:Python134

• tmills/ihmm

  A fork of Jurgen Vangael's Infinite HMM matlab code

  Language:Matlab12307

• AnomDiffDB/DB

  Language:Python6023

• bmelinden/uncertainSPT

  Estimate and use localization uncertainty for single particle tracking and localization microscopy.

  Language:MATLAB3300

• AnDiChallenge/first_steps_in_anomalous_diffusion

  Language:Jupyter Notebook20

• davidalejogarcia/PL_HagerLab

  Matlab scripts to analyze SMT dwell times. "Power-law behaviour of transcription factor dynamics at the single-molecule level implies a continuum affinity model"

  Language:MATLAB21

• AliviGitHub/MoNet

  MotionNet or MoNet: Physics informed deep learning code to classify the behavior and extract alpha exponent for trajectories from single particle tracking experiments

  Language:Python1

• mlomholt/andi

  Language:MATLAB11

• mlomholt/fbm

  Language:Matlab1

• romanbarth/Hi-D

  MATLAB files for the Hi-D approach presented in Shaban, H.; Barth, R.; Recoules, L.; Bystricky, K.; Hi-D: Nanoscale mapping of nuclear dynamics in single living cells. Genome Biology (2020). Released under the GNU General Public License.

  Language:MATLAB13

• Samudrajit11/NS_DD

  Language:Matlab1

• whluo/MILTracker_Matlab_Version

  This code is the Matlab implementation of visual tracker based on multiple instance learning by Babenko et al.

  Language:MATLAB1100