https://github.com/demfier/reading-list
List of articles to read
https://github.com/demfier/reading-list
Last synced: 4 months ago
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List of articles to read
- Host: GitHub
- URL: https://github.com/demfier/reading-list
- Owner: Demfier
- Created: 2019-11-19T03:19:03.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2019-11-20T19:57:16.000Z (over 6 years ago)
- Last Synced: 2025-07-26T05:04:23.970Z (11 months ago)
- Size: 4.88 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# reading-list
## Read
## To Read
* [Tutorial: Deep Latent-Variable Models for NLP](https://github.com/harvardnlp/DeepLatentNLP/blob/master/tutorial_deep_latent.pdf)
* [Latent Normalizing Flows for Discrete Sequences](https://arxiv.org/pdf/1901.10548.pdf)
* [Multi-turn Dialogue Response Generation in an Adversarial Learning Framework](https://www.aclweb.org/anthology/W19-4114.pdf)
* [Distilling Translations with Visual Awareness](https://www.aclweb.org/anthology/P19-1653.pdf)
* [Latent Variable Model for Multi-modal Translation](https://www.aclweb.org/anthology/P19-1642.pdf)
* [Topic Modeling with Wasserstein Autoencoders](https://www.aclweb.org/anthology/P19-1640.pdf)
* [Towards Generating Long and Coherent Text with Multi-Level Latent Variable Models](https://www.aclweb.org/anthology/P19-1200.pdf)
* [Avoiding Latent Variable Collapse with Generative Skip Models](https://arxiv.org/pdf/1807.04863.pdf)
* [Variational Auto-Decoder: Neural Generative Modeling from Partial Data](https://arxiv.org/pdf/1903.00840v2.pdf)
* [Landscape of Deep Generative Models](http://wilkeraziz.github.io/pages/landscape)
* [ML notes and papers](https://github.com/wilkeraziz/notes)
* [Wilkar Aziz teachings](http://wilkeraziz.github.io/teaching.html)
* [Understanding the Effect of Textual Adversaries in Multimodal Machine Translation](https://www.aclweb.org/anthology/D19-6406.pdf)
* [Conditionally Learn to Pay Attention for Sequential Visual Task](https://arxiv.org/pdf/1911.04365.pdf)
## Code
* [Deep Generative Models for NLP (proababll lab)](https://github.com/probabll/dgm4nlp/)