CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

Publication-ready NN-architecture schematics.

A simple, extensible LLM client for Emacs

Simple, unified interface to multiple Generative AI providers

High-Performance Symbolic Regression in Python and Julia

Scientific poster written entirely in org-mode

Official repository of the xLSTM.

Deep Reinforcement Learning: Zero to Hero!

Distributed Asynchronous Hyperparameter Optimization in Python

PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

An API standard for single-agent reinforcement learning environments, with popular reference environments and related utilities (formerly Gym)

Open standard for machine learning interoperability

Python programs, usually short, of considerable difficulty, to perfect particular skills.

Replicate some results in Farrell, S., & Lewandowsky, S. (2018). Computational modeling of cognition and behavior. Cambridge University Press.

Code and website accompanying Farrell & Lewandowsky's (2017) book

Download an entire website from the Wayback Machine.

python port: An Introduction to Bayesian Data Analysis for Cognitive Science

yewtube, forked from mps-youtube , is a Terminal based YouTube player and downloader. No Youtube API key required.

WebGazer.js: Scalable Webcam EyeTracking Using User Interactions

Run ruff, isort, pyupgrade, mypy, pylint, flake8, and more on Jupyter Notebooks

WebGazer.js: Scalable Webcam EyeTracking Using User Interactions

👩‍💻👨‍💻 Awesome cheatsheets for popular programming languages, frameworks and development tools. They include everything you should know in one single file.

A Git credential helper that securely authenticates to GitHub, GitLab and BitBucket using OAuth.

An awesome list of websites about minimal web design and copious swearing

Large language model code completion for Emacs

Bayesian Modeling and Probabilistic Programming in Python

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphic…

self-studying the Sutton & Barto the hard way