Code for paper "The Markovian Thinker: Architecture-Agnostic Linear Scaling of Reasoning"

Multi-tool for semantic search

Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation

Physics-Informed Neural networks for Advanced modeling

Solve forward and inverse problems related to partial differential equations using finite basis physics-informed neural networks (FBPINNs)

Advanced NETCONF Explorer: Graphical Explorer for NETCONF / YANG and GNMI/GRPC Telemetry & Java NETCONF 1.1 client library

YANG data modeling language library

Transform YANG models into pydantic datastructures

The workflow orchestrator core repository

Generate audiobooks from e-books, voice cloning & 1158+ languages!

Virtual whiteboard for sketching hand-drawn like diagrams

[EMNLP2025] "LightRAG: Simple and Fast Retrieval-Augmented Generation"

Get your documents ready for gen AI

LDB: A Large Language Model Debugger via Verifying Runtime Execution Step by Step (ACL'24)

NETCONF implementation in Go.

Evaluation tools for time series machine learning algorithms.

Whisper command line client compatible with original OpenAI client based on CTranslate2.

Interact with your documents using the power of GPT, 100% privately, no data leaks

This is a PyTorch implementation of ConvTran

Get up and running with OpenAI gpt-oss, DeepSeek-R1, Gemma 3 and other models.

User-friendly AI Interface (Supports Ollama, OpenAI API, ...)

🎤📄 An innovative tool that transforms audio or video files into text transcripts and generates concise meeting minutes. Stay organized and efficient in your meetings, and get ready for Phase 2 wher…

Multiple pooling operators and transformations for fast and effective time series classification

A toolkit for time series machine learning and deep learning

Vectorized backtester and trading engine for QuantRocket

Zipline, a Pythonic Algorithmic Trading Library

Zipline, a Pythonic Algorithmic Trading Library

Code for Machine Learning for Algorithmic Trading, 2nd edition.

[AAAI-23 Oral] Official implementation of the paper "Are Transformers Effective for Time Series Forecasting?"