NeuralCDE VS torchdyn

Compare NeuralCDE vs torchdyn and see what are their differences.

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NeuralCDE torchdyn
1 1
570 1,270
- 3.2%
0.0 5.2
over 1 year ago 20 days ago
Python Jupyter Notebook
Apache License 2.0 Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

NeuralCDE

Posts with mentions or reviews of NeuralCDE. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning NeuralCDE yet.
Tracking mentions began in Dec 2020.

torchdyn

Posts with mentions or reviews of torchdyn. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning torchdyn yet.
Tracking mentions began in Dec 2020.

What are some alternatives?

When comparing NeuralCDE and torchdyn you can also consider the following projects:

torchsde - Differentiable SDE solvers with GPU support and efficient sensitivity analysis.

sktime-dl - DEPRECATED, now in sktime - companion package for deep learning based on TensorFlow

deepxde - A library for scientific machine learning and physics-informed learning

bittensor - Internet-scale Neural Networks

monodepth2 - [ICCV 2019] Monocular depth estimation from a single image

handwritten-multi-digit-number-recognition - Recognize handwritten multi-digit numbers using a CRNN model trained with synthetic data.

deep-learning-v2-pytorch - Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101

hyperlearn - 2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.

sense - Enhance your application with the ability to see and interact with humans using any RGB camera.

PyTorch-Guide - PyTorch Guide

signatory - Differentiable computations of the signature and logsignature transforms, on both CPU and GPU. (ICLR 2021)