Showing 1381-1400 of 1,591 projects
Introductory examples and tutorials on deep generative modeling techniques like VAEs, GANs, and score-based models.
A PyTorch-based framework for solving constrained optimization problems, physics-informed ML, and parametric model predictive control.
A collection of open-source papers from the MICCAI conference, focused on deep learning and medical imaging.
A tutorial that takes developers from no deep learning knowledge to implementing GPT using PyTorch.
A PyTorch Lightning code guideline and template for building deep learning projects.
Deep learning framework for the Julia programming language, focused on building AI-powered applications.
A curated collection of resources on applying Transformers to medical imaging tasks like segmentation, classification, and synthesis.
A comprehensive list of papers on World Models, a technique for general video generation, embodied AI, and autonomous driving.
A powerful math formula OCR tool that supports handwritten, Chinese-mixed formulas and simple symbol reasoning.
A high-performance and accurate license plate detection library built using Yolov5 and ncnn.
Real-time photorealistic talking-head animation system built with Python and deep learning.
A lightweight adapter that bridges the Segment Anything Model (SAM) with medical imaging applications.
A curated list of the most impressive AI research papers for developers interested in cutting-edge AI.
Physics-based Deep Learning Book v0.3 - a comprehensive resource for AI developers
A PyTorch implementation of the Capsule Graph Neural Network (CapsGNN) for graph classification tasks.
Lectures for a deep learning course at the University of Liรจge.
A curated list of resources on large language model-based text-to-SQL for developer productivity and database access.
Replicable multi-agent reinforcement learning library with support for PyTorch, Ray, and RLlib.
A PyTorch library for monocular depth estimation using deep learning techniques.
A comprehensive guide to learning about Graph Neural Networks (GNNs), a powerful deep learning technique for processing graph-structured data.
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