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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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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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The goal is to study DL method for BCI classification:
- [Deep learning with convolutional neural networks for EEG decoding and visualization](https://pubmed.ncbi.nlm.nih.gov/28782865/), 1744 citati…
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Learning local feature descriptors with triplets and shallow convolutional neural networks, BMVC2016
Comparative Evaluation of Hand-Crafted and Learned Local Features, CVPR2017
Universal Corresponde…
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# Reference
**paper**
- 09/2018 [Searching for Efficient Multi-Scale Architectures for Dense Image Prediction](https://arxiv.org/abs/1809.04184)
- 10/2018 [Fast Neural Architecture Search of Compac…
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Jax-0.4.31: Runtime: 27.06 seconds
https://colab.research.google.com/drive/1EsFY1St8Y2ZNBZ9UXTa9FDWrjPDdTU4U?usp=sharing
Jax-0.4.33: Runtime: 84.91 seconds
https://colab.research.google.com/drive…
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#### Related to Community Detection
- Large graph visualization using community detection
- Circling a set of nodes with a boundary such that obstruction is proportional to BFS
- [Nearly Balanced…
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Hi,
I noticed the links provided for the papers associated to the Compact and Dense U-Net architectures are wrong.
Both links are pointing to the ResNet paper "[Deep Residual Learning for Image Reco…
uvbkq updated
3 years ago
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## Description:
This issue proposes an enhancement to the Kolmogorov-Arnold Networks (KAN) architecture that involves the development of an automated method for converting trained models into symboli…