Pytorch
Showing 36 of 294 projects
A toolkit for evaluating and monitoring machine learning models in clinical healthcare settings.
A PyTorch-based toolbox for graph reliability, focusing on adversarial attacks, defenses, and robustness techniques for graph neural networks.
A Python library for building, training, and deploying spiking neural networks with support for multiple simulation backends and neuromorphic hardware.
A pre-configured Docker image with deep learning frameworks, data science tools, and GPU support for rapid environment setup.
A Python package and tutorial collection for signal processing and machine learning, built on NumPy and SciPy.
A curated archive of pre-trained computer vision models for object detection, face recognition, fire detection, and more.
An open-source prompt guard model that detects prompt injection attacks while mitigating over-defense against benign inputs.
A modern, fast, and modular deep learning and machine learning framework for Python built on PyTorch.
A PyTorch-based Python library for energy-based machine learning models, including Restricted Boltzmann Machines and Deep Belief Networks.
A PyTorch deep generative model for integrating and imputing single-cell multimodal data with missing modalities.
A fungal image classification project using ResNet to identify mushroom species from citizen science and expert sources.
A PyTorch-based tool for training custom DeepDream models using GoogleNet and custom image datasets.
A machine learning approach for rapid, pathologist-level cell type annotation from spatial proteomics data like MIBI and CODEX.
An open-source solution for the Airbus Ship Detection Challenge, providing a benchmark and base for ship detection in satellite imagery.
A PyTorch-based project for classifying chest X-rays and localizing pathologies using Grad-CAM with fine-tuned CNN models.
A BERT-based model that detects six types of toxicity in text comments, deployable as a Docker container.
An interpretable multi-task deep neural network for single-cell multi-omics integration and cross-modal analysis.
A PyTorch-based framework providing implementations of state-of-the-art deep learning models for computer vision tasks.
An easy-to-use PyTorch library for faster computer vision model development and training.
Deploy a neural network model that transfers artistic styles from one image to another using a ResNet-based architecture.
A PyTorch framework for reinforcement learning research, focused on reproducibility and fast experimentation.
An open-source solution for the Google AI Open Images Object Detection Challenge, providing a RetinaNet-based benchmark with experiment tracking.
A ROS2 template node for running PyTorch C++ models, enabling real-time inference in robotics applications.
A Python module for creating convolutional autoencoders to model background error covariance in variational data assimilation.
A pre-trained image classifier that recognizes 365 different scene and location types using a ResNet18 model fine-tuned on Places365.
A framework for automated cryptographic primitive classification using dynamic binary instrumentation and deep learning.
A Docker-based starter kit providing pre-configured Jupyter notebook environments for machine learning with TensorFlow, PyTorch, and essential libraries.
A Python package for 3D single-cell shape analysis using geometric deep learning on point clouds and voxels.
A graphical interface for segmenting yeast cells in microscopy images using convolutional neural networks.
Flax (JAX) and PyTorch implementations of the DeepSeek-R1-Distill-Qwen-1.5B language model with weight conversion utilities.
PyTorch implementation of twin graph neural networks with similarity augmentation for drug response prediction using protein-protein associations.
A neural network-based tool that suggests lemma names for Coq verification projects by analyzing serialized statements and elaborated terms.
A bilateral awareness network combining transformers and convolutions for semantic segmentation of very fine resolution urban scene images.
A research project exploring multilingual BERT models for Named Entity Recognition in German and English using the CoNLL-2003 dataset.
A ROS2 template node for running PyTorch C++ models with CUDA support in a Docker environment.
A deep learning model that predicts drug response by fusing multi-omics data with graph convolutional networks.
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