dnn_from_scratch VS deepxde

Compare dnn_from_scratch vs deepxde and see what are their differences.

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dnn_from_scratch deepxde
1 2
29 2,356
- -
0.0 8.6
almost 3 years ago about 17 hours ago
Python Python
- GNU Lesser General Public License v3.0 only
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.

dnn_from_scratch

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

deepxde

Posts with mentions or reviews of deepxde. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-05-24.

What are some alternatives?

When comparing dnn_from_scratch and deepxde you can also consider the following projects:

HyperGAN - Composable GAN framework with api and user interface

NeuralPDE.jl - Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation

ALAE - [CVPR2020] Adversarial Latent Autoencoders

diffrax - Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/

guesslang - Detect the programming language of a source code

PaddlePaddle - PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)

open-lpr - Open Source and Free License Plate Recognition Software

deep_learning_and_the_game_of_go - Code and other material for the book "Deep Learning and the Game of Go"

Mask-RCNN-TF2 - Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow 2.0

pymadcad - Simple yet powerful CAD (Computer Aided Design) library, written with Python.

t81_558_deep_learning - T81-558: Keras - Applications of Deep Neural Networks @Washington University in St. Louis

NeuralCDE - Code for "Neural Controlled Differential Equations for Irregular Time Series" (Neurips 2020 Spotlight)