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# Matryoshka Representation Learning Review
blog도 개설한겸 논문한편을 리뷰해보고자 한다. 정말 오랜만에 작성하는 리뷰이다. 이 논문의 제목은
Matryoshka Representation Learning 으로 Neurips'22 에 accept된 논문이다.
학습된 representation (예를 들어 encoder…
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The links at https://github.com/google-research/google-research/tree/master/remote_sensing_representations#dataset-splits are broken.
I'm trying to reproduce these now using the provided notebook, …
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For this notebook (https://github.com/AllenCell/benchmarking_representations/blob/main/src/br/notebooks/fig3_pcna.ipynb) to run, the references to the data in the pcna pointcloud folder does not inclu…
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See["Causal Representation Learning from Multiple Distributions: A General Setting"](https://arxiv.org/abs/2402.05052) for one description of the problem setup in the case of purely observational data…
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### Model Name
MolE molecular embeddings
### Model Description
MolE is a foundation model for chemistry developed by Recursion. It combines geometric deep learning with transformers, to learn a mea…
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This issue aims to model simulation agent parameters using a DNA and genes-inspired approach. By structuring agent parameters, such as “learning rate,” as genes within a genome, we can encode, decode,…
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**What is one hot encoding?**
One hot encoding is one way to prepare data for an algorithm and improve prediction for categorical data, which are variables made up of label values. With one-hot, we c…
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### 論文へのリンク
[[arXiv:1711.00937] Neural Discrete Representation Learning](https://arxiv.org/abs/1711.00937)
### 著者・所属機関
Aaron van den Oord, Oriol Vinyals, Koray Kavukcuoglu
- DeepMind
##…
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Thanks for shareing the wonderful work of UV-Net.
I have a question about the unsupervised representation learning proposed in section 4.2.3 of the paper of UV-Net.
I tried an unsupervised represent…
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## 一言でいうと
Data Augmentationを用いる強化学習で、事前に表現学習を行いその後に通常通りの強化学習を行う研究。表現学習は時系列が近い状態を近いと(Augmentationをかけても)認識できるよう対照学習を行う。その後強化学習を行う。初回からEnd2Endより高い性能を観測
### 論文リンク
https://arxiv.org/abs/2009.08319…