Pure Numpy Implementation of the Coherent Point Drift Algorithm
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Updated
Aug 8, 2023 - Python
Pure Numpy Implementation of the Coherent Point Drift Algorithm
A Python package following the scikit-learn API for model-based clustering and generalized mixture modeling (latent class/profile analysis) of continuous and categorical data. StepMix handles missing values through Full Information Maximum Likelihood (FIML) and provides multiple stepwise Expectation-Maximization (EM) estimation methods.
Code for the algorithms in the paper: Vaibhav B Sinha, Sukrut Rao, Vineeth N Balasubramanian. Fast Dawid-Skene: A Fast Vote Aggregation Scheme for Sentiment Classification. KDD WISDOM 2018
Python library to implement advanced trading strategies using machine learning and perform backtesting.
[MICCAI 2022 Best Paper Finalist] Bayesian Pseudo Labels: Expectation Maximization for Robust and Efficient Semi Supervised Segmentation
Code and data for the KDD2020 paper "Learning Opinion Dynamics From Social Traces"
CLIP-seq Analysis of Multi-mapped reads
An implementation of the expectation maximization algorithm
Learning Diffusion Priors from Observations by Expectation Maximization
GPU traning of a Gaussian Mixture (with online EM)
Learning Bayesian Network parameters using Expectation-Maximisation
This project aims to implement a algorithm to do a grapheme-phoneme alignment task.
Modelling Bach Chorales using Factorial Hidden Markov Models
Sparse Bayesian Multidimensional Item Response Theory
Modeling correlated count data
Weighted Expectation-Maximization for sparse GMM Training that was a sub-algorithm in my thesis.
My works for EE 511 - Simulation Methods For Stochastic Systems - Spring 2018 - Graduate Coursework at USC - Dr. Osonde A. Osoba
Codebase of the CASE@EMNLP 2022 paper: Causality Detection using Multiple Annotation Decision.
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