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https://arxiv.org/abs/2409.19096
```bib
@article{sirohi2024enhancing,
title={Enhancing Robustness of Graph Neural Networks through p-Laplacian},
author={Sirohi, Anuj Kumar and Halder, Subhanu …
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This issue focuses on introducing a **proofreading mechanism** for the cell division process in the simulation. In this system, each cell is represented as a neural network, and its "genetic material"…
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This feature aims to enhance the current genome encoding model by integrating an **autoencoder** to compress and encode neural network weights into a latent vector. The autoencoder will replace the di…
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Develop a Python script using TensorFlow or Keras to generate unique artwork using neural networks. The tool should allow users to customize art styles, colors, and patterns.
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Hi while creating the neural network dynamically gives flexibility, at the end probably more than 95% of the NAM models are NAM "STANDARD" (the network with up to 512 dilation rates and 2 layers).
Is…
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## 레퍼런스 논문
1. Graph Clustering with Graph Neural Networks (DMoN)
- paper : [https://arxiv.org/abs/2006.16904](https://arxiv.org/abs/2006.16904)
- code : [https://github.com/google-research/go…
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We aim to implement a system that leverages distillation and quantization to create a "child" neural network by combining parameters from two "parent" neural networks. The child network should inherit…
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Hi! I don't know if i got it right reading documentation and examples. However my question is: in order to train a neural network in full bartch mode (that is, using all the available instancdes), is …
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https://arxiv.org/pdf/2207.08200
this paper provides a different way to optimize the priors using distance aware priors.
Maybe i can try to implement it.
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## Feature
### Description
One idea of the original concept were 3-dimensional neural networks. Theoretically it should better mix different inputs, but it was never tested, because other basic …