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"
Sum Product Flow: An Easy and Extensible Library for Sum-Product Networks
Implementation of Switch Transformers from the paper: "Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity"
Bayesian inference for Gaussian mixture model with some novel algorithms
PiKV: KV Cache Management System for Mixture of Experts [Efficient ML System]
PyTorch implementation of the mixture distribution family with implicit reparametrisation gradients.
Python (pip) package for fitting mixtures of Student's t-distributions using either maximum likelihood (EM) or Bayesian methodology (variational mean-field)
A friendly Python library for multistate analysis with MICS and MBAR
A Fast and Simplified Python Library for Uncertainty Estimation
Plackett-Luce Regression Mixture Model
CSE 601 Data mining and bioinformatics
A library for efficient uncovering of latent cluster labels in functional data from Gaussian process mixtures.
Python, MATLAB, and JAGS code associated with the preprint, "Beyond rates: Time-varying dynamics of high frequency oscillations as a biomarker of the seizure onset zone." (2021)
This program provides a look into the application of neural networks to predict the mass excess for nuclei which have yet to be experimentally measured.
MachineLearning
CSE 569, Fall 2019 Fundamentals of Statistical Learning Course at ASU
Inflated Discrete Choice Models
Python implementation of a complex-valued version of the expectation-maximization (EM) algorithm for fitting Mixture of Factor Analyzers (MFA).
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