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NBoulle avatar

NBoulle/RationalNets

0
View on GitHub↗
30 stars·5 forks·Python·MIT·20 views

RationalNets

We consider neural networks with rational activation functions. The choice of the nonlinear activation function in deep learning architectures is crucial and heavily impacts the performance of a neural network. We establish optimal bounds in terms of network complexity and prove that rational…

Features

  • 3D Shape Analysis - Rational neural network layers for improved function approximation.

Star history

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How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

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Projects sharing features with RationalNets

These projects share indexed features with RationalNets. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • fpthink/pdgnfpthink avatar

    fpthink/PDGN

    28View on GitHub↗

    by Le Hui, Rui Xu, Jin Xie, Jianjun Qian, and Jian Yang, details are in paper.

    Python
    View on GitHub↗28
  • hansen7/occohansen7 avatar

    hansen7/OcCo

    239View on GitHub↗

    This repository is the official implementation of paper: "Unsupervised Point Cloud Pre-training via Occlusion Completion"

    Python
    View on GitHub↗239
  • itailang/samplenetitailang avatar

    itailang/SampleNet

    392View on GitHub↗

    Created by Itai Lang, Asaf Manor, and Shai Avidan from Tel Aviv University.

    Python
    View on GitHub↗392
  • a2zadeh/variational-autodecoderA

    A2Zadeh/Variational-Autodecoder

    0View on GitHub↗
    View on GitHub↗0
Compare all 25 related projects→

Frequently asked questions

What does nboulle/rationalnets do?

We consider neural networks with rational activation functions. The choice of the nonlinear activation function in deep learning architectures is crucial and heavily impacts the performance of a neural network. We establish optimal bounds in terms of network complexity and prove that rational…

What are the main features of nboulle/rationalnets?

The main features of nboulle/rationalnets are: 3D Shape Analysis.

Which projects share features with nboulle/rationalnets?

Projects with overlapping indexed features include: fpthink/pdgn — by Le Hui, Rui Xu, Jin Xie, Jianjun Qian, and Jian Yang, details are in paper. hansen7/occo — This repository is the official implementation of paper: "Unsupervised Point Cloud Pre-training via Occlusion… itailang/samplenet — Created by Itai Lang, Asaf Manor, and Shai Avidan from Tel Aviv University. lorenmt/shape-adaptor — This repository contains the source code to support the paper: Shape Adaptor: A Learnable Resizing Module, by Shikun… luost26/dmrdenoise — [Project Page] [Paper] [Code]. a2zadeh/variational-autodecoder.