Life & fun · alternatives · 2026

24 alternatives to A Higher-Order Graph Convolutional Layer, NeurIPS 2018 (PyTorch)

An implementation of "MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing" (ICML 2019). - benedekrozemberczki/MixHop-and-N-GCN

Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. A Higher-Order Graph Convolutional Layer, NeurIPS 2018 (PyTorch) launched in 2019; newer entries below may have overtaken it.

1. 1
   MixHop: Higher-Order Graph Convolutional Architectures, ICML 2019▲5

   An implementation of "MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing" (ICML 2019). - benedekrozemberczki/MixHop-and-N-GCN

   2019 · github.com · its alternatives →

2. 2GC
   Graph Convolutional Networks – Intro to neural networks on graphs▲106

   Many important real-world datasets come in the form of graphs or networks: social networks, knowledge graphs, protein-interaction networks, the World Wide Web, etc. (just to name a few). Yet, until recently, very little attention has been devoted to the generalization of neural...

   2016 · tkipf.github.io · its alternatives →

3. 3
   Tensorflow Implementation of Graph Convolutional Network▲5

   Tensorflow implementation of Graph Convolutional Network - shagunsodhani/pregel

   2017 · github.com · its alternatives →

4. 4
   Sonnet▲134

   A new library for constructing neural networks from DeepMind

   2017 · deepmind.google · its alternatives →

5. 5
   TensorFlow 1.0▲80

   Open-source machine learning library by Google

   2018 · tensorflow.org · its alternatives →

6. 6
   TensorFire▲99

   Blazing-fast in-browser neural networks

   2017 · tenso.rs · its alternatives →

7. 7
   Talking Machines: OpenAI and Gaussian Processes▲56

   Featuring Ilya Sutskever, director of research for OpenAI

   2016 · thetalkingmachines.com · its alternatives →

8. 8AL
   A library to build graph neural networks in Keras▲8

   Spektral: Graph Neural Networks in TensorFlow 2 and Keras

   2019 · danielegrattarola.github.io · its alternatives →

9. 9
   Graphlearn-for-PyTorch, distributed graph learning on PyTorch▲9

   Hello HN, We are pleased to introduce you graphlearn-for-pytorch (https://github.com/alibaba/graphlearn-for-pytorch), an open-source distributed graph neural network library based on PyTorch and compatible with PyG. Our library is designed to make it easy for developers to build and train large-scale graph models in a distributed environment. With graphlearn-for-pytorch, you can leverage GPUs to accelerate graph sampling and utilize UVA to reduce the overheads of feature collection. Following a scalable design, graphlearn-for-pytorch supports training GNN models on…

   2023 · github.com · its alternatives →

10. 10
    TensorFlow▲17

    An Open Source Library for Machine Intelligence (by Google)

    2015 · tensorflow.org · its alternatives →

11. 11
    Faster R-CNN object detector implemented in PyTorch and TensorFlow 2▲15

    Fresh and (I think) clean implementations of Faster R-CNN in PyTorch and TensorFlow 2/Keras. I wanted to learn about object detectors and decided to understand and implement a foundational model in the field, Faster R-CNN (elements of which are still used in modern models to this day), using the paper alone. That proved to be more difficult than expected and I had to relent and take a peak at existing implementations to fill in some important gaps. I've documented my struggles and learnings in the README for others to benefit from. I also wanted to solidify my understanding of…

    2022 · github.com · its alternatives →

12. 12
    Parallel Multi-Scale Network Embedding with Walklets▲5

    A lightweight implementation of Walklets from "Don't Walk Skip! Online Learning of Multi-scale Network Embeddings" (ASONAM 2017). - benedekrozemberczki/walklets

    2019 · github.com · its alternatives →

13. 13
    Deep learning without gradient descent, 500 layers, no skip connections▲5

    Code that reproduces experiments from a scientific paper - xolod7/polyharmonic-cascade

    Jan 2026 · github.com · its alternatives →

14. 14
    A collection of graph classification methods (kernels, deep learning)▲8

    A collection of important graph embedding, classification and representation learning papers with implementations. - benedekrozemberczki/awesome-graph-classification

    2020 · github.com · its alternatives →

15. 15
    KANN – mid-scale deep learning and autodiff in ANSI C (4 files; 4k LOC)▲5

    A lightweight C library for artificial neural networks - attractivechaos/kann

    2018 · github.com · its alternatives →

16. 16BH
    Beating Hinton et al.'s capsule net with fewer params and less training▲14

    Hello HN, I recently posted a work-in-progress paper, along with code necessary for replicating all its results, at: https://github.com/glassroom/heinsen_routing Among other things, the code in this repo outperforms Hinton et al.'s recent state-of-the-art result in visual recognition[0] while requiring fewer parameters and an order-of-magnitude fewer training epochs. Most of the original research we do at work tends to be either proprietary in nature or tightly coupled to internal code, so we cannot share it with the world. In this case, however, I was able to remove all…

    2019 · its alternatives →

17. 17
    TensorFlow Sequence-to-Sequence▲6

    A general-purpose encoder-decoder framework for Tensorflow

    2017 · google.github.io · its alternatives →

18. 18
    Graph Wavelet Neural Network, ICLR 2019 (PyTorch)▲6

    A PyTorch implementation of "Graph Wavelet Neural Network" (ICLR 2019) - benedekrozemberczki/GraphWaveletNeuralNetwork

    2019 · github.com · its alternatives →

19. 19
    "What's This?" – machine learning with react-native and tensorflow▲5

    A smart camera app using react-native and tensorflow - northfoxz/whatsthis

    2016 · github.com · its alternatives →

20. 20
    Reimplementing PyTorch from scratch (MLP, CNN) to learn the internals▲5

    Implement classic neural networks from scratch without using nn.Module, to deeply understand PyTorch and model principles. - geyuxu/nn-from-scratch

    Feb 2026 · github.com · its alternatives →

21. 21
    TensorFlow▲3

    A Neural Network Playground

    2016 · playground.tensorflow.org · its alternatives →

22. 22
    GradientsGuru▲8

    collection of beautiful gradients and blend image effects

    2018 · its alternatives →

23. 23
    PyTorch▲5

    Tensors and dynamic neural networks in Python

    2017 · pytorch.org · its alternatives →

24. 24
    An Automatic Drawing AI in Python▲5

    ICCV2019 - Learning to Paint With Model-based Deep Reinforcement Learning - hzwer/ICCV2019-LearningToPaint

    2019 · github.com · its alternatives →

Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →