Pytorch
Showing 36 of 294 projects
Multi-dimensional arrays (tensors) and numerical definitions for Elixir, enabling machine learning and scientific computing.
A lightweight deep learning library with a functional API for composing models, compatible with PyTorch, TensorFlow, and MXNet.
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.
An accessible, general-purpose platform for understanding, managing, deploying, and automating adaptive experiments using Bayesian and bandit optimization.
Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.
An open-source deep learning API and server written in C++ that supports multiple backends like PyTorch, TensorRT, and TensorFlow for training and inference.
A Python library for outlier, adversarial, and drift detection in machine learning models, supporting tabular, text, image, and time series data.
Automatic neural architecture search and hyperparameter optimization for PyTorch, focusing on tabular data and time series forecasting.
HyperLearn provides 2-2000x faster machine learning algorithms with 50% less memory usage, optimized for all hardware.
A modular toolkit for machine learning, natural language processing, and text generation with TensorFlow and PyTorch versions.
A large-scale dataset of object-centric video clips with 3D bounding box annotations and AR metadata for 3D object detection research.
A flow-based generative network for fast, high-quality speech synthesis from mel-spectrograms.
A generalist algorithm for cellular segmentation with human-in-the-loop training and superhuman generalization across diverse microscopy images.
A Python library for audio data augmentation to improve the robustness of audio machine learning models.
A modular, high-throughput PyTorch framework for deep reinforcement learning research, supporting policy gradient, deep Q-learning, and Q-function policy gradient algorithms.
A deep learning system for accurate protein structure and interaction prediction using a three-track neural network.
An open source Python library and framework for building computer vision models on satellite, aerial, and large imagery sets.
PyGAD is a Python library for building genetic algorithms and optimizing machine learning models with Keras and PyTorch support.
A Python library for constructing differentiable convex optimization layers in PyTorch, JAX, and MLX using CVXPY.
A toolkit and library for developing, evaluating, and reproducing reinforcement learning algorithms.
An end-to-end Python pipeline for semantic segmentation of aerial and satellite imagery to extract features like buildings and roads.
An end-to-end deep learning system for reconstructing complete 3D scenes (geometry and semantics) from posed 2D images.
A deep learning model for protein sequence design that generates amino acid sequences for given protein backbones.
A Python package for fine-tuning and generating text with GPT-2 and GPT Neo models using PyTorch and Hugging Face Transformers.
Clean PyTorch implementations of imitation and reward learning algorithms for reinforcement learning.
An end-to-end 3D object detection network that uses deep point set networks and Hough voting to directly detect objects in point clouds.
A collection of models, callbacks, and datasets to extend PyTorch Lightning for applied AI/ML research and production.
A lightweight library providing PyTorch training tools and utilities to simplify and standardize training loops.
A Python library for simulating spiking neural networks (SNNs) using PyTorch, geared towards biologically inspired machine learning.
TensorLy: Tensor Learning in Python.
A Python library for deep probabilistic modeling and analysis of single-cell and spatial omics data.
A Python library for offline deep reinforcement learning with support for state-of-the-art algorithms and user-friendly APIs.
A unified framework for implementing and training deep learning models on tabular data using PyTorch and PyTorch Lightning.
An all-in-one framework for training state-of-the-art computer vision models, covering pretraining, fine-tuning, and distillation.
A Python library for automated hyperparameter optimization and model evaluation with TensorFlow, Keras, and PyTorch.
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