libsusa/susa

High Performance Computing (HPC) and Signal Processing Framework

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henry-prior/jax-rl

JAX implementations of core Deep RL algorithms

Language: Python - Size: 354 KB - Last synced at: about 2 years ago - Pushed at: about 3 years ago - Stars: 62 - Forks: 9

gbroques/naive-bayes

A Python implementation of Naive Bayes from scratch.

Language: Python - Size: 61.5 KB - Last synced at: 15 days ago - Pushed at: about 7 years ago - Stars: 38 - Forks: 27

MikeS96/bayes_statististics

Bayesian Statistics MOOC by Coursera - Solutions in Python

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KeplerGO/oktopus

🐙: Maximum likelihood model estimation using scipy.optimize

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hyeonsangjeon/disparity-based-space-vagriant-image-deblurring

“Disparitybased space-variant image deblurring,” Signal Processing: Image Communication, vol. 28, no. 7, pp. 792–808, 2013.

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jolideco/jolideco

A Python package for Poisson joint likelihood deconvolution

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EricLu1218/Machine_Learning

2022 NTHU EE655000 Machine Learning Course Projects (include Maximum A Posteriori Estimation, Linear Regression, Neural Network Image Classification)

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prakHr/NeuralNetworksAndFuzzyLogic

[College Course] - Course: BITS F312 Neural Network and Fuzzy Logic

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farhad-dalirani/Disparity-Map-Reconstruction-PGM

Probabilistic Graphical Models for Stereo Disparity Map Reconstruction by Factor Graph and Belief Propagation Maximum A Posteriori

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ctpeterson/SwissFit

General-purpose library for fitting models to data with correlated Gaussian-distributed noise

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mozanunal/notebook-ml-map-comparasion

It is a jupyter notebook which examine the varience and bias parameters of maximum likelihood and maximum a posteriori approaches for biomedical imaging.

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kyomangold/ETH-MachineLearning

Repository for the code of the "Introduction to Machine Learning" (IML) lecture at the "Learning & Adaptive Systems Group" at ETH Zurich.

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TheUnsolvedDev/ProbabilisticMadness

Statistics and Machine Learning in depth analysis with Tensorflow Probability

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hrshtv/Bayesian-Image-Denoising

A MAP-MRF Framework for Image Denoising

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amirian/xeggora

An inference engine for Markov Logic

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hrshtv/MRF-Segmentation-Graph-Cuts

An implementation of "Exact Maximum A Posteriori Estimation for Binary Images" (D. Greig, B. Porteous and A. Seheult)

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prash030/pattern_recognition_projects

This repository consists of the codes that I wrote for implementing various pattern recognition algorithms

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hyzhak/mle

Machine Learning: Maximum Likelihood Estimation (MLE)

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Taabannn/intro-ml

This repository has been created just for warm-up in machine learning and there are my simulation files of UT-ML course HWs.

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sayarghoshroy/Image-Classification-Formulations

Insights and Analysis - Using Various Deep Learning Architectures on Image Classification Datasets

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animesharma/NaiveBayes-MAP-MLE

Categorial Naive Bayes MLE and MAP Estimators for EMNIST dataset

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jackyan540/cs181-homework3

Spring 2021 Machine Learning (CS 181) Homework 3

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eskinderit/MLvsMAP

A brief comparison of the weights computation for a linear classifer using Maximum Likelihood (ML) and Maximum aPosteriori (MAP)

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bhavyanarang/SML_Coding_Assignments

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IChowdhury01/ECE-302-Probability-Models-and-Stochastic-Processes

Projects for ECE-302: Probability Models & Stochastic Processes

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RaczeQ/naive-bayes-classifier

A Python implementation of Naive Bayes from scratch. Repository influenced by https://github.com/gbroques/naive-bayes

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violetguos/intro_machine_learning

🅱️achine learning

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