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## Overview
This project aims to predict loan defaults using deep learning techniques. The system utilizes Multi-Layer Perceptron (MLP), Convolutional Neural Networks (CNN), and Recurrent Neural Ne…
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## 一言でいうと
RNNはLSTMとかの構造をいじるのが主流になっているけれど、入力を工夫した方がいいんじゃない？ということで、入力列を通常の文字列とそこから「粗い(Coarse)」情報を抽出したものとを並列で入力するモデルを提案している(=multi resolution)。
### 論文リンク
https://arxiv.org/abs/1606.00776
### …
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### RNN 이해를 위한 자료:
* Understanding Hidden Memories of Recurrent Neural Networks
Yao Ming, Shaozu Cao, Ruixiang Zhang, Zhen Li, Yuanzhe Chen, Yangqiu Song, Huamin Qu
* https://kevinzakka.github.io/2…
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Abstract: We present Compositional Attention Networks, a novel fully differentiable neural network architecture, designed to facilitate explicit and expressive reasoning. While many types of neural ne…
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```
docs/
├── README.md # Overview of the documentation structure
├── getting-started/
│ ├── introduction.md # Introduction to AIBuddies and AI
│ …
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### Pitch
Hi, I think Mastodon needs to add a tutorial that appears at the beginning, once you log in for the first time. Something simple that indicates the most used features. This would make it mu…
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https://arxiv.org/pdf/1511.06939.pdf
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### 🚀 Feature
I suggest expanding the system's recurrent components by introducing various recurrent neural networks (RNNs) like vanilla RNN, GRU, and maybe some lesser-know networks like LMU, and ct…
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**Is your feature request related to a problem? Please describe.**
LSTMs are capable of capturing long-term dependencies, and attention mechanisms help the model focus on relevant parts of the input …
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In the neuroscience literature, the idea of recurrent networks are important as that architecture is thought to have important properties. One example is being able to instantiate content-addressable …
whock updated
9 years ago