Deep Learning
Showing 36 of 937 projects
A Python package providing gradient-based optimizers specifically designed for machine learning scenarios.
A deep learning model using generative adversarial networks for fast compressed sensing MRI reconstruction.
A Torch-based deep learning project for breaking CAPTCHA systems using CNN and RNN architectures.
A Python machine learning and informatics suite for analyzing, mining, and modeling chemical and materials data.
A Keras implementation of Microsoft's R-NET neural network for question answering on the SQuAD dataset.
A collection of examples demonstrating how to use Comet.ml for machine learning experiment tracking across various Python frameworks.
A transformer-based model for unconditional and conditional molecular generation using GPT architecture trained on chemical datasets.
A deep learning model for joint perception and motion prediction in autonomous driving using bird's eye view maps.
A collection of Jupyter notebooks demonstrating TensorFlow Lite model quantization, conversion, and optimization techniques for deep neural networks.
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MATLAB code for inverting deep neural network representations to visualize and understand learned features from CVPR 2015.
A simple and powerful neural network library for Python with a MATLAB-like API and flexible configuration.
A TensorFlow C API wrapper enabling machine learning in server-side Swift applications.
A high-performance tensor library for the V programming language, providing n-dimensional data structures and linear algebra operations.
A Python library that builds neural networks with minimal boilerplate code for PyTorch and TensorFlow.
A modular NLP framework for extracting information from French clinical notes, compatible with spaCy and PyTorch.
Unofficial JAX/Flax implementations of deep learning research papers for vision transformers and other architectures.
An open-source CAD framework for designing, simulating, and deploying deep neural networks on embedded platforms.
A deep learning approach that unifies global place recognition and local 6DoF pose refinement for robust relocalization in large-scale 3D point clouds.
A deep learning model that classifies sounds in 10-second audio clips into 527 categories from the AudioSet ontology.
A deep learning model using transformer architecture to predict compound-protein interactions from molecular and protein sequences.
A curated archive of research papers and resources on generative modeling, covering GANs, image synthesis, 3D generation, and applications.
Open-source implementation of the winning solution for the 2018 Data Science Bowl Kaggle competition using PyTorch and U-Net.
An open-source starter solution for the Kaggle Toxic Comment Classification Challenge, providing ready-to-use machine learning pipelines for detecting online harassment.
A pure, immutable module system for JAX that replaces PyTorch-style imperative coding with declarative parameter trees.
.NET Standard bindings for Apache MXNet, providing C# developers with NumPy-compatible APIs for machine learning model development, training, and deployment.
A deep bilinear attention network framework with adversarial domain adaptation for interpretable drug-target interaction prediction.
A type-safe, functional ONNX API and backend for deep learning and classical machine learning in Scala 3.
A PyTorch Geometric extension library for signed and directed graph neural networks, embedding, and clustering methods.
A TensorFlow implementation of hierarchical attentive recurrent neural networks for single object tracking in videos.
A fast, flexible, and compact deep learning framework for Julia that runs on CPU and CUDA GPU.
A TensorFlow-based neural network model for generating descriptive captions from images using Flickr30K and MSCOCO datasets.
Open-source software for deep learning-based analysis and visualization of whole slide images in digital pathology.
A JAX transform that implements LoRA (Low-Rank Adaptation) for efficient fine-tuning of large models with minimal memory overhead.
Keras implementation of Pix2pix for image-to-image translation using conditional adversarial networks.
A deep learning-based, threshold-agnostic, subpixel-accurate 2D and 3D spot detection method for fluorescence microscopy and spatial transcriptomics.
A compact spiking neural network library built on JAX and Haiku, offering high-performance training via surrogate gradient descent and neuroevolution.
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