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Hi, many thanks for your work on this amazing package.
There is a paper called ["Spatial Graph Convolutional Networks"](https://arxiv.org/pdf/1909.05310), with accompanying [PyTorch code](https://…
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https://arxiv.org/pdf/1906.01629
```bib
@misc{gasse2019exactcombinatorialoptimizationgraph,
title={Exact Combinatorial Optimization with Graph Convolutional Neural Networks},
author…
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Quantum-inspired
- Reinforcement learning for quantum circuit design (Allan, Zhiyuan, Thomas)
- Reinforcement learning for drug discovery (Dannong)
- Approximating wave functions using transformer-…
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**Paper**
Enhanced Multi-Channel Graph Convolutional Network for Aspect Sentiment Triplet Extraction
**Introduction**
The paper introduces a method that uses the Graph Convolutional Network for …
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# Ligand-based model
## Graph
Featurization:
- [x] Running
Model:
- [ ] Running
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Venue: ICML 2019
Summary: Proposes a simplified linear graph neural network architecture (GCN with non-linearity layers removed). New architecture is significantly faster than the state of the art mo…
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I am very interested in your research _Ensemble Manifold Regularized Multi-Modal Graph Convolutional Network for Cognitive Ability Prediction_, and _Integrated Brain Connectivity Analysis with fMRI, D…
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Given the recent popularity of graph convolutional neural networks (i.e. https://github.com/tkipf/gcn), would it be worth implementing a swift paradigmatic version? I have a semi-working version, but …
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1.(HMMR) Learning 3d human dynamics from video(2019)
temporal encoder: **1D temporal** convolutional layers, **precompute** the image features on each frame, get current and ±∆t frames prediction.
c…
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## 一言でいうと
グラフにおいて「新しいノードをどう扱うか」という問題にチャレンジした研究。SNSやアイテム推薦における新規アイテム問題ではこの点が顕著だが、既存の研究では固定的なグラフを扱うのが大半だった。VAEをベースとして、順次ノードが追加されていく時系列の生成モデルという形でアプローチをしている
### 論文リンク
https://arxiv.org/abs/1903.…