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Suggested list of courses would be:
- An introduction to deep learning **
- How to train a neural network
- Regularisation in neural networks
- Deep Bayesian neural networks
- Conv…
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Hey John! Here's the curriculum that I've worked on in the past. It's a bit less focused on language models as a sole topic, and more on modern ML from a broad perspective.
- Essential Concepts of …
zmaas updated
2 months ago
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## 一言でいうと
今後より人間に近しいタスクを行っていくには、推論方法をより一般化したものにしていく必要があるという提言。CNNは局所的な情報から、RNNは系列的な情報からしか推論できないため、グラフ型が適しているとしている。そこでグラフネットワークを新しい構造単位として使うための定義を行っている。
### 論文リンク
https://arxiv.org/abs/1806.01…
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Traceback (most recent call last):
File "D:/Code/CodePycharm/Deep_Learning/segment/Efficient-Segmentation-Networks-master/train.py", line 409, in
train_model(args)
File "D:/Code/CodePychar…
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[Graph neural network-inspired kernels for gaussian processes in semi-supervised learning](https://arxiv.org/abs/2302.05828)
```bib
@article{niu2023graph,
title={Graph neural network-inspired ker…
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What do you think of adding Graph Convolutional Networks in a new section on ML and deep learning?
Here are some references:
* https://tkipf.github.io/graph-convolutional-networks/
* https://gi…
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### Initial Concept
1. **Symbolic Assignments**:
- We started by assigning symbolic meanings to prime numbers, connecting them to concepts like cognition, cosmos, life, human expression, informat…
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Read the papers in [Deep Learning’s Most Important Ideas](https://www.kdnuggets.com/2020/09/deep-learnings-most-important-ideas.html).
- [x] Tackling ImageNet with AlexNet and Dropout
- [x] [I…
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- [Graph-based Neural Networks](https://github.com/sungyongs/graph-based-nn)
- [Graph Convolution Networks](http://tkipf.github.io/graph-convolutional-networks/) by Thomas Kipf
- [Geometric Deep Lea…
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**Please check the [Github](https://github.com/zezhishao/MTS_Daily_ArXiv) page for a better reading experience and more papers.**
## Time Series
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