kumsh
Ph.D Student at NC State University. Focus on scalable Bayesian deep learning, probabilistic framework, tuning, and optimization
NC State UniversityRaleigh, NC
Pinned Repositories
horovod
Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
bokeh
Interactive Web Plotting for Python
edward2
A simple probabilistic programming language.
fiber
Distributed Computing for AI Made Simple
Gen
A general-purpose probabilistic programming system with programmable inference
HIP
HIP : Convert CUDA to Portable C++ Code
intro_dgm
An Introduction to Deep Generative Modeling: Examples
numpyro
Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.
Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
Stan.jl
WIP: Stan.jl v6 refactors CmdStan v6. Stan.jl illustrates the usage of the new 'single method' packages, e.g. StanSample, StanOptimize, etc.
kumsh's Repositories
kumsh/Gen
A general-purpose probabilistic programming system with programmable inference
kumsh/intro_dgm
An Introduction to Deep Generative Modeling: Examples
kumsh/edward2
A simple probabilistic programming language.
kumsh/fiber
Distributed Computing for AI Made Simple
kumsh/numpyro
Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.
kumsh/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
kumsh/Stan.jl
WIP: Stan.jl v6 refactors CmdStan v6. Stan.jl illustrates the usage of the new 'single method' packages, e.g. StanSample, StanOptimize, etc.
kumsh/120-Data-Science-Interview-Questions
Answers to 120 commonly asked data science interview questions.
kumsh/apex
A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch
kumsh/data_split_in_Beam
Apache Beam for splitting the data
kumsh/DeepLearningExamples
Deep Learning Examples
kumsh/deeprob
deep probabilistic framework
kumsh/double_mnist_analysis
Analysing double mnist data to understand if any relational knowledge is present
kumsh/edward
A probabilistic programming language in TensorFlow. Deep generative models, variational inference.
kumsh/gen-quickstart
Docker file for building Gen and Jupyter notebooks for tutorials and case studies
kumsh/greta
simple and scalable statistical modelling in R
kumsh/indigo
:ramen: Minimalist Jekyll Template
kumsh/keras-tuner
Hyperparameter tuning for humans
kumsh/LiteratureDL4Graph
kumsh/minimal-mistakes
:triangular_ruler: Jekyll theme for building a personal site, blog, project documentation, or portfolio.
kumsh/OpenSKAI
kumsh/pixel-cnn-pp
Pytorch Implementation of OpenAI's PixelCNN++
kumsh/pml2-book
Probabilistic Machine Learning: Advanced Topics
kumsh/project-monai.github.io
project monai website https://monai.io/
kumsh/pyprob
A PyTorch-based library for probabilistic programming and inference compilation
kumsh/pyprobml
Python code for "Probabilistic Machine learning" book by Kevin Murphy
kumsh/pyro
Deep universal probabilistic programming with Python and PyTorch
kumsh/RapiD
An extension of the iD map editor for mapping with AI-generated features.
kumsh/resampling_dgms
kumsh/TuringTutorials
Educational material and tutorials for the Turing language