Raschka-research-group/coral-pytorch
quality grade D, 45 out of 100CORAL and CORN implementations for ordinal regression with deep neural networks.
- stars
- 277
- stars gained this week
- —this week
- forks, open issues and contributors
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Core deep-learning frameworks and libraries for pretraining and distributed training.
Signals: deep-learning, neural-network, pytorch, tensorflow, jax, distributed-training, training, deepspeed
2,697 results
CORAL and CORN implementations for ordinal regression with deep neural networks.
Code for "Graph Neural Network on Electronic Health Records for Predicting Alzheimer’s Disease"
Code for paper "Synthesizing the preferred inputs for neurons in neural networks via deep generator networks"
Cockpit: A Practical Debugging Tool for Training Deep Neural Networks
Relation-Shape Convolutional Neural Network for Point Cloud Analysis (CVPR 2019 Oral & Best paper finalist)
Enabling easy statistical significance testing for deep neural networks.
A PyTorch implementation of " EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks."
Implementation of MolCLR: "Molecular Contrastive Learning of Representations via Graph Neural Networks" in PyG.
Code for the paper "A Theoretically Grounded Application of Dropout in Recurrent Neural Networks"
Neural Network Tools: Converter and Analyzer. For caffe, pytorch, draknet and so on.
The Simple and Efficient Semi-Supervised Learning Method for Deep Neural Networks
OpenRec is an open-source and modular library for neural network-inspired recommendation algorithms
The Prodigy optimizer and its variants for training neural networks.
DHGNN source code for IJCAI19 paper: "Dynamic Hypergraph Neural Networks"
pytorch implementation of "Distilling a Neural Network Into a Soft Decision Tree"
A deep neural network architecture for low-latency audio processing
TensorFlow 2.0 implementation of Maziar Raissi's Physics Informed Neural Networks (PINNs).
Building and training artificial neural networks (regression or classification) using the genetic algorithm.
Bases on Leaf images we are trying to predict plant disease using convolutional neural network. PyTorch implementation
Rank Consistent Ordinal Regression for Neural Networks with Application to Age Estimation
NNgen: A Fully-Customizable Hardware Synthesis Compiler for Deep Neural Network
A simple deep neural network implemented in C++,based with OpenCV Mat matrix class
Convolutional Recurrent Neural Network (CRNN) for image-based sequence recognition using Pytorch
High-level batteries-included neural network training library for Pytorch
24,523 repositories in the index in total.