dmarx/dmarx-github-stars huggingface dataset:
Repository: xuedong/machine-learning-summer-schools
Description: Curated materials for different machine learning related summer schools
Language: Jupyter Notebook
Topics: automatic-differentiation, causal-inference, deep-learning, deep-reinforcement-learning, gaussian-processes, generative-adversarial-network, interpretability, kernel-methods, machine-learning, mcmc, multi-agent, multi-armed-bandits, natural-language-processing, optimal-transport, optimization, probabilistic-graphical-models, reinforcement-learning, statistics, transfer-learning, variational-inference
Repository: jaanli/variational-autoencoder
Description: Variational autoencoder implemented in tensorflow and pytorch (including inverse autoregressive flow) 
Language: Python
Topics: autoregressive-neural-networks, deep, deep-learning, deep-neural-networks, learning, machine-learning, probabilistic-graphical-models, pytorch, tensorflow, unsupervised-learning, vae, variational-autoencoder, variational-inference
Homepage: https://jaan.io/what-is-variational-autoencoder-vae-tutorial/
Repository: TuringLang/Turing.jl
Description: Bayesian inference with probabilistic programming.
Language: Julia
Topics: artificial-intelligence, bayesian-inference, bayesian-neural-networks, bayesian-statistics, hamiltonian-monte-carlo, hmc, julia-language, machine-learning, mcmc, probabilistic-graphical-models, probabilistic-inference, probabilistic-models, probabilistic-programming, turing
Homepage: https://turinglang.org