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- [GBDT based on LightGBM (Guolin Ke, et al. NIPS 2017)](examples/benchmarks/LightGBM/) - [GBDT based on LightGBM (Guolin Ke, et al. NIPS 2017)](examples/benchmarks/LightGBM/)
- [GBDT based on Catboost (Liudmila Prokhorenkova, et al. NIPS 2018)](examples/benchmarks/CatBoost/) - [GBDT based on Catboost (Liudmila Prokhorenkova, et al. NIPS 2018)](examples/benchmarks/CatBoost/)
- [MLP based on pytorch](examples/benchmarks/MLP/) - [MLP based on pytorch](examples/benchmarks/MLP/)
- [LSTM based on pytorch (Sepp Hochreiter, et al. Neural omputation 1997)](examples/benchmarks/LSTM/) - [LSTM based on pytorch (Sepp Hochreiter, et al. Neural computation 1997)](examples/benchmarks/LSTM/)
- [GRU based on pytorch (Kyunghyun Cho, et al. 2014)](examples/benchmarks/GRU/) - [GRU based on pytorch (Kyunghyun Cho, et al. 2014)](examples/benchmarks/GRU/)
- [ALSTM based on pytorch (Yao Qin, et al. IJCAI 2017)](examples/benchmarks/ALSTM) - [ALSTM based on pytorch (Yao Qin, et al. IJCAI 2017)](examples/benchmarks/ALSTM)
- [GATs based on pytorch (Petar Velickovic, et al. 2017)](examples/benchmarks/GATs/) - [GATs based on pytorch (Petar Velickovic, et al. 2017)](examples/benchmarks/GATs/)

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# Gated Recurrent Unit (GRU)
* Paper: [Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation](https://aclanthology.org/D14-1179.pdf).

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# Long Short-Term Memory (LSTM)
* Paper: [Long Short-Term Memory](https://direct.mit.edu/neco/article-abstract/9/8/1735/6109/Long-Short-Term-Memory?redirectedFrom=fulltext).

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# Localformer

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# Multi-Layer Perceptron (MLP)

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# TCN
* Code: [https://github.com/locuslab/TCN](https://github.com/locuslab/TCN)
* Paper: [An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling](https://arxiv.org/abs/1803.01271).

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# TabNet
* Code: [https://github.com/dreamquark-ai/tabnet](https://github.com/dreamquark-ai/tabnet)
* Paper: [TabNet: Attentive Interpretable Tabular Learning](https://arxiv.org/pdf/1908.07442.pdf).

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# Transformer
* Code: [https://github.com/tensorflow/tensor2tensor](https://github.com/tensorflow/tensor2tensor)
* Paper: [Attention is All you Need](https://proceedings.neurips.cc/paper/2017/file/3f5ee243547dee91fbd053c1c4a845aa-Paper.pdf).