ALAE VS dnn_from_scratch

Compare ALAE vs dnn_from_scratch and see what are their differences.

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ALAE dnn_from_scratch
1 1
3,494 29
- -
0.0 0.0
over 3 years ago almost 3 years ago
Python Python
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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.

ALAE

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

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.

What are some alternatives?

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

jukebox - Code for the paper "Jukebox: A Generative Model for Music"

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

simsiam-cifar10 - Code to train the SimSiam model on cifar10 using PyTorch

HyperGAN - Composable GAN framework with api and user interface

generative-inpainting-pytorch - A PyTorch reimplementation for paper Generative Image Inpainting with Contextual Attention (https://arxiv.org/abs/1801.07892)

guesslang - Detect the programming language of a source code

lightweight-gan - Implementation of 'lightweight' GAN, proposed in ICLR 2021, in Pytorch. High resolution image generations that can be trained within a day or two

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

denoising-diffusion-pytorch - Implementation of Denoising Diffusion Probabilistic Model in Pytorch

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

torch-metrics - Metrics for model evaluation in pytorch

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