Pytorch
Showing 36 of 294 projects
A general-purpose PyTorch codebase for 3D object detection with state-of-the-art model implementations and multi-dataset support.
Official repository for Big Transfer (BiT) models, providing pre-trained visual representations for efficient transfer learning across computer vision tasks.
Type annotations and runtime checking for PyTorch tensor shape, dtype, layout, and names.
A foundational PyTorch library for training deep learning models, serving as the core engine for the OpenMMLab ecosystem.
An open-source differentiable dense SLAM library for PyTorch, enabling gradient flow from map outputs to sensor inputs.
A fast, modular PyTorch reference implementation for training and evaluating semantic segmentation models.
A curated collection of open-source computer vision pre-trained models across TensorFlow, Keras, PyTorch, Caffe, and MXNet frameworks.
A modular deep reinforcement learning framework in PyTorch for research and application, featuring ready-to-use algorithms and reproducible experiments.
State-of-the-art pre-trained transformer language models for protein sequences, enabling tasks like structure prediction and function annotation.
A PyTorch implementation of self-supervised monocular depth estimation using 3D packing for high-resolution, real-time depth prediction.
A deep learning JavaScript library built from scratch with PyTorch-like syntax and GPU acceleration via GPU.js.
An open-source library providing chest X-ray datasets, pre-trained models, and tools for medical imaging research and analysis.
A Python framework for portfolio optimization using deep learning to allocate investment weights in a single forward pass.
A deep learning library for drug-target interaction, drug property, protein-protein interaction, drug-drug interaction, and protein function prediction in bioinformatics.
An autoML framework and toolkit for automating machine learning tasks on graph-structured data.
An audio processing toolbox using PyTorch 1D convolutional neural networks for on-the-fly spectrogram generation with trainable kernels.
A PyTorch implementation for super fast and accurate 3D object detection using LiDAR point clouds, featuring an anchor-free approach.
A modular Python library for Reinforcement Learning with support for PyTorch, JAX, NVIDIA Warp, and multiple environment interfaces.
A PyTorch framework for efficient 3D semantic and panoptic segmentation using superpoint-based transformer architectures.
A PyTorch framework for training neural learning-to-rank models with flexible loss functions and scoring architectures.
A PyTorch-based framework for training and validating models that produce high-quality embeddings for metric learning and retrieval tasks.
A deep learning-enhanced Kalman filter for accurate vehicle dead reckoning using only an IMU sensor.
A pretrained modeling library for Keras 3 offering simple, flexible, and fast access to models for text, image, and audio tasks.
A benchmarking platform for molecular generation models, providing datasets, implementations, and evaluation metrics for drug discovery research.
A uniform interface to run deep learning models from multiple frameworks like TensorFlow, PyTorch, and Keras in C++ and Python.
A PyTorch implementation of Social GAN for predicting socially acceptable human trajectories using generative adversarial networks.
Convert PyTorch models to Keras (TensorFlow backend) for deployment and interoperability.
A PyTorch implementation of neural style transfer, combining the content of one image with the artistic style of another.
A Ruby deep learning library powered by LibTorch, providing a PyTorch-like API for Ruby developers.
A deep learning library for Ruby that provides a native interface to LibTorch, enabling GPU-accelerated neural network development.
A Python package for applying graph neural networks to molecular graphs and biological networks in life science research.
A benchmark and toolkit for discovering, detecting, recognizing, and tracking UAVs in the wild using RGB and thermal infrared video.
A PyTorch framework for semantic segmentation of large 3D point clouds using superpoint graphs.
A long-range genomic foundation model that processes DNA sequences up to 1 million nucleotides at single nucleotide resolution.
A modular deep learning framework for PyTorch to build neural networks on heterogeneous tabular data.
A convolutional neural network program that identifies inverted Chinese character captchas used by Zhihu for login verification.
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