Implementation of "Lifting from the Deep: Convolutional 3D Pose Estimation from a Single Image"
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Updated
Jan 20, 2022 - Python
Implementation of "Lifting from the Deep: Convolutional 3D Pose Estimation from a Single Image"
Code that might be useful to others for learning/demonstration purposes, specifically along the lines of modeling and various algorithms. **Superseded by the models-by-example repo**.
Sum Product Flow: An Easy and Extensible Library for Sum-Product Networks
Efficient phylogenomic software by maximum likelihood
An extensible C++ library of Hierarchical Bayesian clustering algorithms, such as Bayesian Gaussian mixture models, variational Dirichlet processes, Gaussian latent Dirichlet allocation and more.
◽ <- ⚪ Structural Equation Modeling from a broader context.
Bayesian inference for Gaussian mixture model with some novel algorithms
An unsupervised machine learning algorithm for the segmentation of spatial data sets.
Distributed MCMC Inference in Dirichlet Process Mixture Models (High Performance Machine Learning Workshop 2019)
Morphological Prototyping for Unsupervised Slide Representation Learning in Computational Pathology - CVPR 2024
An HMM and Phylogenetic Placement based Ultra-Fast Taxonomy Assignment Tool for 16S sequencing
Model-based subclonal deconvolution from bulk sequencing.
Implementation of Switch Transformers from the paper: "Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity"
A Collection of Basic Utilities for Statistical Analyses
Implement the Kasahara-Shimotsu Test to decide number of components in Gaussian Mixture Model.
Mixture of experts on convolutional neural network using Keras and Cifar10
Herramientas estadísticas para la investigación
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