Pytorch
Showing 36 of 294 projects
Official repository for Big Transfer (BiT) models, providing pre-trained visual representations for efficient transfer learning across computer vision tasks.
A foundational PyTorch library for training deep learning models, serving as the core engine for the OpenMMLab ecosystem.
Type annotations and runtime checking for PyTorch tensor shape, dtype, layout, and names.
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 deep learning library for drug-target interaction, drug property, protein-protein interaction, drug-drug interaction, and protein function prediction in bioinformatics.
A Python framework for portfolio optimization using deep learning to allocate investment weights in a single forward pass.
An autoML framework and toolkit for automating machine learning tasks on graph-structured data.
A PyTorch implementation for super fast and accurate 3D object detection using LiDAR point clouds, featuring an anchor-free approach.
An audio processing toolbox using PyTorch 1D convolutional neural networks for on-the-fly spectrogram generation with trainable kernels.
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 deep learning-enhanced Kalman filter for accurate vehicle dead reckoning using only an IMU sensor.
A PyTorch-based framework for training and validating models that produce high-quality embeddings for metric learning and retrieval tasks.
A benchmarking platform for molecular generation models, providing datasets, implementations, and evaluation metrics for drug discovery research.
A pretrained modeling library for Keras 3 offering simple, flexible, and fast access to models for text, image, and audio tasks.
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.
A benchmark and toolkit for discovering, detecting, recognizing, and tracking UAVs in the wild using RGB and thermal infrared video.
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 long-range genomic foundation model that processes DNA sequences up to 1 million nucleotides at single nucleotide resolution.
A PyTorch framework for semantic segmentation of large 3D point clouds using superpoint graphs.
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.
A PyTorch and TorchDrug based deep learning library for drug pair scoring, predicting interactions, side effects, and synergy.
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