Awesome list for all things AI, ML and deep learning
Table of Contents
- awesome-ai
Visualizing A Neural Machine Translation Model (Mechanics of Seq2seq Models With Attention)
A model that uses attention to boost the speed with which these models can be trained
http://jalammar.github.io/illustrated-transformer/
The Universal Transformer is an extension to the Transformer models which combines the parallelizability and global receptive field of the Transformer model with the recurrent inductive bias of RNNs, which seems to be better suited to a range of algorithmic and natural language understanding sequence-to-sequence problems.
http://mostafadehghani.com/2019/05/05/universal-transformers/
An algorithmic framework for learning useful representation from highly structured objects such as graphs.
- dgl: Python package built to ease deep learning on graph, on top of existing DL frameworks.
- cdlib: Community Discovery Library - (for networkx and igraph)
- Embedding-Vis
- OpenNE
- Parikh, A.P., Täckström, O., Das, D. and Uszkoreit, J., 2016. A decomposable attention model for natural language inference. arXiv preprint arXiv:1606.01933.
- Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, Ł. and Polosukhin, I., 2017. Attention is all you need. In Advances in neural information processing systems (pp. 5998-6008).
- Devlin, J., Chang, M.W., Lee, K. and Toutanova, K., 2018. Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805.
- The illustrated GPT-2 (Visulaizing Transformer Language Models)
- Transformers from scratch
- Searching for Answer Candidate Passages with Solr and Anserini
- Subramanian et al., 2019. On extractive and abstractive neural document summarization with transformer language models
- Wang et al., 2018. Ontology Alignment in the Biomedical Domain Using Entity Definitions and Context
- Wang et al., 2019., Extracting evidence of supplement-drug interactions from literature
- awesome-pytorch-list
- the-incredible-pytorch
- awesome-ternsorflow
- keras-resources
- DataSciencePython
- DataScienceR
- awesome-deep-learning-papers
- awesome-decision-tree-papers
- awesome-gradient-boosting-papers
- must read papers on graph neural network
- deep learning biology
- awesome-deepbio
- nlp-roadmap
- NLP-progress
- awesome-nlp
- awesome-bert
- awesome-word2vec
- awesome-embedding-models
- NCBI BioNLP Research Group (PI: Zhiyong Lu)
- awesome-bert
- thunlp awesome paper repos
- the super duper NLP repo
- awesome-community-detection
- awesome-graph-classification
- awesome-network-analysis
- awesome-network-embedding
- graph-based-deep-learning-literature
- LiteratureDL4Graph