danaja

awesome-explainable-graph-reasoning

A collection of research papers and software related to explainability in graph machine learning.

trilium

Build your personal knowledge base with Trilium Notes

okrs

🧭 My personal Objectives and Key Results (OKRs), tracked on GitHub

v4

Fourth iteration of my personal website built with Gatsby

boxes

code for box-covering algorithms

hyperbolic-learning

Implemented Machine Learning Algorithms in Hyperbolic Geometry (MDS, K-Means, Support vector machines, etc.)

BayesianStatisticsCourse

PhD-level course at [EMAp](https://emap.fgv.br/en)

scientific-visualization-book

An open access book on scientific visualization using python and matplotlib

ForumMagnum

The development repository for LessWrong2 and the EA Forum, based on Vulcan JS

cleanBib

Probabilistically assign gender and race proportions of first/last authors pairs in bibliography entries

getting-started-with-the-twitter-api-v2-for-academic-research

A course on getting started with the Twitter API v2 for academic research

ggdist

Visualizations of distributions and uncertainty

Nominatim

Open Source search based on OpenStreetMap data

rsiena

An R package for Simulation Investigation for Empirical Network Analysis

HoroPCA

Hyperbolic PCA via Horospherical Projections

metaflow

Open Source Platform for developing, scaling and deploying serious ML, AI, and data science systems

relational-ERM

Software relating to relational empirical risk minimization

causal-network-embeddings

Software and pre-processed data for "Using Embeddings to Correct for Unobserved Confounding in Networks"

did2s

Two-stage Difference-in-Differences package following Gardner (2021)

NYT_Content_Analysis

polis

:milky_way: Open Source AI for large scale open ended feedback

specter

SPECTER: Document-level Representation Learning using Citation-informed Transformers

EconML

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

malmo

Project Malmo is a platform for Artificial Intelligence experimentation and research built on top of Minecraft. We aim to inspire a new generation of research into challenging new problems presented by this unique environment. --- For installation instructions, scroll down to *Getting Started* below, or visit the project page for more information:

annotated_deep_learning_paper_implementations

🧑‍🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

s2orc-doc2json

Parsers for scientific papers (PDF2JSON, TEX2JSON, JATS2JSON)

post--misread-tsne

How to Use t-SNE Effectively

stanza

Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages

allennlp

An open-source NLP research library, built on PyTorch.

agentpy

AgentPy is an open-source framework for the development and analysis of agent-based models in Python.