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High-fidelity performance metrics for generative models in PyTorch
A high-performance GPU database engine built for AI and machine learning workloads.
A curated list of resources for the Conformal Prediction machine learning technique.
A Jupyter Notebook project that leverages OpenAI and ChatGPT to perform hacking-related tasks.
A pure Python implementation of Spiking Neural Networks for tasks like MNIST classification.
Lightweight C/C++ Extended Kalman Filter library with Python for prototyping embedded systems and IoT devices.
A transformer-based model for neighborhood attention, useful for computer vision tasks.
Teaching materials for an applied machine learning course at Cornell Tech, suitable for vibe coders.
ezkl is a Rust-based engine for doing inference on deep learning models and computational graphs in zero-knowledge.
GPU-accelerated deep learning library in Python for building and training neural networks.
A powerful named entity recognition tool for building AI-powered applications in Python.
A structured reasoning framework for AI coding tools like Claude Code, Gemini, Cursor, and Codex.
Matterport3D is a dataset for RGB-D machine learning tasks, especially 3D reconstruction and semantic scene understanding.
Physics-Informed Neural Networks (PINN) Solvers for accelerated simulation and scientific machine learning.
This repository provides materials to learn about hardware-assisted virtualization and its application for high-performance fuzzing.
A common in-memory tensor structure for deep learning frameworks written in C++.
A framework for data augmentation for 2D and 3D image classification and segmentation tasks.
Distribute and run AI workloads on Kubernetes with a Python-based infrastructure toolkit like PyTorch.
A method to increase the speed and lower the memory footprint of existing vision transformers.
A reusable, open-source library for building AI-powered Go game agents in a readable manner.
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