A side project that aims to replicate the Amadeus App shown in Steins;Gate 0.

Use Google Sheets as your no-setup database

code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"

Solutions to exercises and problems from "Introduction to Algorithms", Fourth Edition by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest and Clifford Stein

A Multimodal AI Application Inspired By Steins;Gate 0

[ICRA2024] Stein Variational Guided Model Predictive Path Integral Control: Proposal and Experiments with Fast Maneuvering Vehicles

LABOKit is a modular desktop tool for offline image processing Built with Python (PySide6), it aims to provide a fast, simple, and user-friendly batch-processing workflow with a retro "Steins;Gate" divergence meter aesthetic.

Analyzing real-world news, tries to estimate the current divergence value of the world in Steins;Gate terms.

STEINS;GATE Improvement Patch source code and build automation

An operating system written in Rust

The code accompanying the paper "Developability of Triangle Meshes" by Oded Stein, Eitan Grinspun and Keenan Crane

Unpacker for STEINS;GATE (Steam edition) and STEINS;GATE 0 .mpk content files

A linter for config files with a customizable rule set

dithering for node

「GitをSteins;Gateの世界観を使って説明する」薄い本

A complete guide to the mechanics of Steins;Gate.

A project to implement the algorithms from Introduction to Algorithms (Cormen, Leiserson, Rivest, and Stein) in Python, Ruby and other programming languages.

A toolkit for processing multiplexed tissue images

A fast implementation of the Goemans-Williamson scheme for the prize-collecting Steiner tree / forest problem.

Reimplementation of Steins;Gate visual novel

Prize-Collecting Steiner Forests for Interactomes

Steiner Shallow-Light Tree for VLSI Routing

Code accompanying Steinmetz et al., 2019

Steins;Gate 0 のアマデウスの再現プロジェクトです。

REST, a reinforcement learning framework for constructing rectilinear Steiner Minimum tree (RSMT)

An encryption scheme for text data allowing a server to store, search and return encrypted data without knowing the content of that data. Based off the 2014 research of David Cash, Joseph Jaeger, Stanislaw Jarecki, Charanjit Jutla, Hugo Krawczyk, Marcel-Catalin Rosu, and Michael Steiner

STEINS;GATE 0 Improvement Patch source code and build automation

Steins;Gate text extractor

Official Release of "Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling"

PyTorch implementation of Stein Variational Gradient Descent