Deep Learning
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PyTorch implementation of FlowNet 2.0 for optical flow estimation using deep neural networks.
An open-source Python library for quantum computing, quantum machine learning, and quantum chemistry.
A cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry.
A cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry.
A JAX-based neural network library that provides a simple, object-oriented programming model for building and training models.
An open-source machine learning platform for distributed training, hyperparameter tuning, experiment tracking, and resource management.
A deep learning framework for training image classification models to solve complex captcha and OCR tasks.
A TensorFlow library providing building blocks for implementing Reinforcement Learning agents.
A TensorFlow implementation of neural style transfer for images and videos, blending content and artistic styles using convolutional neural networks.
A simple and versatile framework for object detection and instance recognition with extensive model coverage and distributed training.
A Rust-native port of Hugging Face Transformers providing ready-to-use NLP pipelines and transformer models like BERT, GPT2, and T5.
A curated list of deep learning image classification papers and their code implementations since 2014.
A TensorFlow library for implementing, deploying, and testing Contextual Bandits and Reinforcement Learning algorithms.
A PyTorch library for spatiotemporal signal processing with dynamic and temporal graph neural networks.
A curated list of scientific articles, theses, and reports on deep learning applied to music information retrieval and generation.
A collection of Python notebooks and tools for quantitative finance research, including backtesting, machine learning, and portfolio optimization.
An easy-to-use, scalable hyperparameter optimization framework for Keras models with define-by-run syntax and built-in search algorithms.
A TensorFlow implementation of a neural conversational model (seq2seq) for building deep learning chatbots.
An open-source diffusion model for generating and designing protein structures, including binders, symmetric oligomers, and motif-scaffolded proteins.
A JAX library for neural networks and scientific computing with PyTorch-like syntax and full ecosystem compatibility.
A curated list of research papers, datasets, and resources for anomaly detection in time-series, video, and image data.
A curated list of academic papers, datasets, and resources for image and video deblurring research.
A lightweight deep learning library with a functional API for composing models, compatible with PyTorch, TensorFlow, and MXNet.
An audio library for PyTorch providing data manipulation, transformations, and dataset loaders for machine learning applications.
An interactive online learning platform for computer vision with a comprehensive Chinese ebook, code, and community.
A Python library that extends OpenAI's Whisper to provide accurate word-level timestamps and confidence scores for multilingual speech recognition.
A deep learning project using Keras to build convolutional and recurrent neural networks for high-accuracy captcha recognition.
Convert Caffe deep learning models to TensorFlow format for deployment and inference.
A deep learning framework for research, development, and production with flexible Python API and C++ core.
A TensorFlow library for Learning-to-Rank (LTR) techniques, providing loss functions, metrics, and models for ranking tasks.
A curated collection of academic papers, code, and resources for learning with noisy labels in machine learning.
A benchmarking suite comparing the performance of public convolutional neural network implementations across multiple deep learning frameworks.
Deep neural network to extract structured information from invoice documents with a customizable UI and training tools.
A curated collection of hands-on data science project ideas and resources for learning machine learning and AI concepts.
A curated list of key papers and resources on implicit neural representations, a novel approach to parameterizing signals as continuous functions.
A collection of beginner-friendly TensorFlow tutorials using Jupyter Notebook, covering deep learning fundamentals and practical applications.
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