Maschinelles Lernen · GitHub

Deep survival analysis made easy

The accompanying code for the book "Hands-On Machine Learning with scikit-learn and Scientific Python Toolkits". A practical guide to implementing supervised and unsupervised machine learning algorithms in Python by Tarek Amr

Sketch Your Own GAN: Customizing a GAN model with hand-drawn sketches.

[NeurIPS 2021] Multiscale Benchmarks for Multimodal Representation Learning

🙌Kart of 234+ projects based on machine learning, deep learning, computer vision, natural language processing and all. Show your support by ✨ this repository.

A library for dimensionality reduction on spatial-temporal PDE

Qualcomm Cloud AI SDK (Platform and Apps) enable high performance deep learning inference on Qualcomm Cloud AI platforms delivering high throughput and low latency across Computer Vision, Object Detection, Natural Language Processing and Generative AI models.

World model / VLA / VLM learning library, with aerial robotics as a running thread. 世界模型 / VLA / VLM 学习库（无人机视角）：59 篇文档 · 195 篇论文 · 24 个纯 CPU 可跑 demo

A Real-time Mario Kart 64 AI using ConvNets.

[NeurIPS 2021] [T-PAMI] DynamicViT: Efficient Vision Transformers with Dynamic Token Sparsification

YOLOv7 Object Tracking Using PyTorch, OpenCV and Sort Tracking

:books: 计算机体系架构、嵌入式系统基础与主流编程语言相关内容总结

This repository contains the source codes for the paper "AtlasNet: A Papier-Mâché Approach to Learning 3D Surface Generation ". The network is able to synthesize a mesh (point cloud + connectivity) from a low-resolution point cloud, or from an image.

TorchDR - PyTorch Dimensionality Reduction

• High Performance - Engineered for speed with GPU acceleration, torch.compile support, and optimized algorithms leveraging sparsity and negative sampling.
• Multi-GPU Support - Scale to massive datasets with built-in distributed computing. Use the torchdr CLI or torchrun for easy multi-GPU execution of compatible modules and methods.