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### 論文へのリンク
- [[arXiv:1903.08550] OCGAN: One-class Novelty Detection Using GANs with Constrained Latent Representations](https://arxiv.org/abs/1903.08550)
### 著者・所属機関
Pramuditha Perera, Rames…
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## 一言でいうと
Model Baseの手法で学習を行う際に、環境全体をモデル化するのでなく、局所的なパートだけモデル化して(このとき戦略も線形化する)、戦略の勾配を推定するという手法。これにより環境全体をモデル化する必要なしにModel Baseによる効率的な学習が可能になる。
 into the latent representations (V; dimensi…
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### Description
Learned Sparse Vectors claim to combine the benefits of sparse (i.e. lexical) and dense (i.e. vector) representations
From https://en.wikipedia.org/wiki/Learned_sparse_retrieval:…
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Thanks for your great work. I am curious about your image processing pipeline? I downloaded the apple PNG image from the README, normalized to 0 & 1, and encoded them using the provided sd15_vae_tra…
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**Checklist**
1. I have searched related issues but cannot get the expected help. Yes
2. I have read the FAQ documentation but cannot get the expected help. Yes
I have trained a simclr model on…
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Abstract: Disentangled representations, where the higher level data generative factors are reflected in disjoint latent dimensions, offer several benefits such as ease of deriving invariant representa…
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[Graph contrastive learning with augmentations](https://proceedings.neurips.cc/paper_files/paper/2020/hash/3fe230348e9a12c13120749e3f9fa4cd-Abstract.html)
```bib
@article{you2020graph,
title={Gra…
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> Autoencoders provide a powerful framework for learning compressed representations
by encoding all of the information needed to reconstruct a data point in
a latent code. In some cases, autoencoder…