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Add classical/new architectures #14
Description
Some ideas for figures to add to the PPT
- Linear regression, single-layer neural network
- Multilayer Perceptron with hidden layer
- Backpropagation
- Batch Normalization and alternatives
- Computational Graphs
- Dropout
- CNN - padding, stride, pooling,...
- LeNet
- AlexNet
- VGG
- GoogleNet
- ResNet
- DenseNet
- Memory Networks
- RNN
- Deep RNN
- Bidirectional RNN
- GRU
- LSTM
- Language RNN models
- Backpropagation through time
- Encoder-Decoder Architecture
- Seq2seq with RNN encoder-decoder
- Bearm search and other decoding strategies
- Attention
- Multi-head attention
- Self-attention
- Transformer
- Word2vec/GloVe/Skip-gram/CBOW/BERT/GPT....
- Common/Popular CV/NLP Tasks
List adopted from multiple resources including nlpoverview and d2l.ai which both contain a very solid syllabus.
Please feel free to make suggestions below. If you would like to help, also let me know.
Activity
[-]Add classical architectures[/-][+]Add classical/new architectures[/+]heany commentedon Jun 25, 2021
Maybe, the generative adversarial networks and graph neural networks should be included in the list.
narutomst commentedon Sep 16, 2021
Deep Belief Networks
nashid commentedon Jun 11, 2022
Can we Graph Neural Network models like GCN, GAT, GGNN, GraphSage, etc?
nashid commentedon Jun 11, 2022
Including Contrastive Representation Learning models would be great!