MArpogaus

NEAT

generalized_orthogonalization

mlflow-migrator

NormalizingFlowNetwork

Bayesian and Maximum Likelihood Implementation of the Normalizing Flow Network (NFN): https://arxiv.org/abs/1907.08982

UMNN

Implementation of Unconstrained Monotonic Neural Network and the related experiments. These architectures are particularly useful for modelling monotonic transformations in normalizing flows.

bunkerweb

🛡️ Make your web services secure by default !

ruff

An extremely fast Python linter and code formatter, written in Rust.

ts-movement

Emacs 29+ minor mode for syntax tree navigation using Tree Sitter

uci-datasets

UCI datasets from the MAF paper

comint-mime

Display graphics and other MIME attachments in Emacs shells

code-cells.el

Emacs utilities for code split into cells, including Jupyter notebooks

pyvinecopulib

A Python library for vine copula models

modus-themes

Highly accessible themes for GNU Emacs, conforming with the highest standard for colour contrast between background and foreground values (WCAG AAA).

lsp-snippet

eglot-tempel

bridge for tempel templates with eglot

awesome-emacs

a curated list of Emacs resources

LLMsPracticalGuide

A curated list of practical guide resources of LLMs (LLMs Tree, Examples, Papers)

openstef-reference

Deploy the entire OpenSTEF stack on your machine. Provides a reference implementation of the OpenSTEF stack including datamodels, databases and UI

openstef

Automated Machine Learning pipelines. Builds the Open Short Term Energy Forecasting package.

deeptrafo

awesome-chatgpt

Selected ChatGPT demos, tools, articles, and more ✨

FlatColor-16

This is a simple gtk3 theme based on FlatColor by deviantfero

FlatColor

This is a simple gtk3 theme based on FlatColor by deviantfero

ontram-paper

Repository accompanying arXiv:2010.08376

localzero-generator-core

dl_book

legend

flowtorch

This library would form a permanent home for reusable components for deep probabilistic programming. The library would form and harness a community of users and contributors by focusing initially on complete infra and documentation for how to use and create components.

pytorch-normalizing-flows

Normalizing flows in PyTorch. Current intended use is education not production.

awesome-normalizing-flows

Awesome resources on normalizing flows.

d2l-en

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.