citations.bib

@inproceedings{GoogleTensorFlow,
  title={Tensorflow: A system for large-scale machine learning},
  author={Abadi, Mart{\'\i}n and Barham, Paul and Chen, Jianmin and Chen, Zhifeng and Davis, Andy and Dean, Jeffrey and Devin, Matthieu and Ghemawat, Sanjay and Irving, Geoffrey and Isard, Michael and others},
  booktitle={12th $\{$USENIX$\}$ Symposium on Operating Systems Design and Implementation ($\{$OSDI$\}$ 16)},
  pages={265--283},
  year={2016}
}

@article{paszke2019pytorch,
  title={Pytorch: An imperative style, high-performance deep learning library},
  author={Paszke, Adam and Gross, Sam and Massa, Francisco and Lerer, Adam and Bradbury, James and Chanan, Gregory and Killeen, Trevor and Lin, Zeming and Gimelshein, Natalia and Antiga, Luca and others},
  journal={Advances in neural information processing systems},
  volume={32},
  year={2019}
}

@misc{franccois2017deep,
  title={Deep learning with Python},
  author={Fran{\c{c}}ois, Chollet},
  year={2017},
  publisher={Manning Publications Company}
}

@inproceedings{glorot2010understanding,
  title={Understanding the difficulty of training deep feedforward neural networks},
  author={Glorot, Xavier and Bengio, Yoshua},
  booktitle={Proceedings of the thirteenth international conference on artificial intelligence and statistics},
  pages={249--256},
  year={2010}
}

@inproceedings{glorot2011deep,
  title={Deep sparse rectifier neural networks},
  author={Glorot, Xavier and Bordes, Antoine and Bengio, Yoshua},
  booktitle={Proceedings of the fourteenth international conference on artificial intelligence and statistics},
  pages={315--323},
  year={2011}
}

@article{lecun2015deep,
  title={Deep learning},
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  journal={nature},
  volume={521},
  number={7553},
  pages={436--444},
  year={2015},
  publisher={Nature Publishing Group}
}

@book{goodfellow2016deep,
  title={Deep learning},
  author={Goodfellow, Ian and Bengio, Yoshua and Courville, Aaron},
  year={2016},
  publisher={MIT press}
}

@article{hinton2006fast,
  title={A fast learning algorithm for deep belief nets},
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}

@article{hochreiter1997long,
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  publisher={MIT Press}
}

@article{kingma2014adam,
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  year={2014}
}

@article{lecun1995convolutional,
  title={Convolutional networks for images, speech, and time series},
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  journal={The handbook of brain theory and neural networks},
  volume={3361},
  number={10},
  pages={1995},
  year={1995}
}

@article{fukushima1980neocognitron,
  title={Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position},
  author={Fukushima, Kunihiko},
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  volume={36},
  number={4},
  pages={193--202},
  year={1980},
  publisher={Springer}
}

@article{mcculloch1943logical,
  title={A logical calculus of the ideas immanent in nervous activity},
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  journal={The bulletin of mathematical biophysics},
  volume={5},
  number={4},
  pages={115--133},
  year={1943},
  publisher={Springer}
}

@inproceedings{nair2010rectified,
  title={Rectified linear units improve restricted boltzmann machines},
  author={Nair, Vinod and Hinton, Geoffrey E},
  booktitle={Proceedings of the 27th international conference on machine learning (ICML-10)},
  pages={807--814},
  year={2010}
}

@article{srivastava2014dropout,
  title={Dropout: a simple way to prevent neural networks from overfitting},
  author={Srivastava, Nitish and Hinton, Geoffrey and Krizhevsky, Alex and Sutskever, Ilya and Salakhutdinov, Ruslan},
  journal={The journal of machine learning research},
  volume={15},
  number={1},
  pages={1929--1958},
  year={2014},
  publisher={JMLR. org}
}

@inproceedings{bui2018neural,
  title={Neural graph learning: Training neural networks using graphs},
  author={Bui, Thang D and Ravi, Sujith and Ramavajjala, Vivek},
  booktitle={Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining},
  pages={64--71},
  year={2018},
  organization={ACM}
}

@inproceedings{sabour2017dynamic,
  title={Dynamic routing between capsules},
  author={Sabour, Sara and Frosst, Nicholas and Hinton, Geoffrey E},
  booktitle={Advances in neural information processing systems},
  pages={3856--3866},
  year={2017}
}

@article{devlin2018bert,
  title={Bert: Pre-training of deep bidirectional transformers for language understanding},
  author={Devlin, Jacob and Chang, Ming-Wei and Lee, Kenton and Toutanova, Kristina},
  journal={arXiv preprint arXiv:1810.04805},
  year={2018}
}

@article{wang2018glue,
  title={Glue: A multi-task benchmark and analysis platform for natural language understanding},
  author={Wang, Alex and Singh, Amanpreet and Michael, Julian and Hill, Felix and Levy, Omer and Bowman, Samuel R},
  journal={arXiv preprint arXiv:1804.07461},
  year={2018}
}

@article{williams2017broad,
  title={A broad-coverage challenge corpus for sentence understanding through inference},
  author={Williams, Adina and Nangia, Nikita and Bowman, Samuel R},
  journal={arXiv preprint arXiv:1704.05426},
  year={2017}
}

@inproceedings{redmon2016you,
  title={You only look once: Unified, real-time object detection},
  author={Redmon, Joseph and Divvala, Santosh and Girshick, Ross and Farhadi, Ali},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={779--788},
  year={2016}
}

@inproceedings{lin2014microsoft,
  title={Microsoft coco: Common objects in context},
  author={Lin, Tsung-Yi and Maire, Michael and Belongie, Serge and Hays, James and Perona, Pietro and Ramanan, Deva and Doll{\'a}r, Piotr and Zitnick, C Lawrence},
  booktitle={European conference on computer vision},
  pages={740--755},
  year={2014},
  organization={Springer}
}

@inproceedings{goodfellow2014generative,
  title={Generative adversarial nets},
  author={Goodfellow, Ian and Pouget-Abadie, Jean and Mirza, Mehdi and Xu, Bing and Warde-Farley, David and Ozair, Sherjil and Courville, Aaron and Bengio, Yoshua},
  booktitle={Advances in neural information processing systems},
  pages={2672--2680},
  year={2014}
}

@article{radford2015unsupervised,
  title={Unsupervised representation learning with deep convolutional generative adversarial networks},
  author={Radford, Alec and Metz, Luke and Chintala, Soumith},
  journal={arXiv preprint arXiv:1511.06434},
  year={2015}
}

@inproceedings{karras2019style,
  title={A style-based generator architecture for generative adversarial networks},
  author={Karras, Tero and Laine, Samuli and Aila, Timo},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages={4401--4410},
  year={2019}
}

@article{karras2019analyzing,
  title={Analyzing and improving the image quality of stylegan},
  author={Karras, Tero and Laine, Samuli and Aittala, Miika and Hellsten, Janne and Lehtinen, Jaakko and Aila, Timo},
  journal={arXiv preprint arXiv:1912.04958},
  year={2019}
}

@article{karras2020training,
  title={Training generative adversarial networks with limited data},
  author={Karras, Tero and Aittala, Miika and Hellsten, Janne and Laine, Samuli and Lehtinen, Jaakko and Aila, Timo},
  journal={Advances in Neural Information Processing Systems},
  volume={33},
  pages={12104--12114},
  year={2020}
}

@article{odena2016semi,
  title={Semi-supervised learning with generative adversarial networks},
  author={Odena, Augustus},
  journal={arXiv preprint arXiv:1606.01583},
  year={2016}
}

@article{mikolov2013efficient,
  title={Efficient estimation of word representations in vector space},
  author={Mikolov, Tomas and Chen, Kai and Corrado, Greg and Dean, Jeffrey},
  journal={arXiv preprint arXiv:1301.3781},
  year={2013}
}

@article{barto1983neuronlike,
  title={Neuronlike adaptive elements that can solve difficult learning control problems},
  author={Barto, Andrew G and Sutton, Richard S and Anderson, Charles W},
  journal={IEEE transactions on systems, man, and cybernetics},
  number={5},
  pages={834--846},
  year={1983},
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}

@article{lillicrap2015continuous,
  title={Continuous control with deep reinforcement learning},
  author={Lillicrap, Timothy P and Hunt, Jonathan J and Pritzel, Alexander and Heess, Nicolas and Erez, Tom and Tassa, Yuval and Silver, David and Wierstra, Daan},
  journal={arXiv preprint arXiv:1509.02971},
  year={2015}
}

@article{weston2015towards,
  title={Towards ai-complete question answering: A set of prerequisite toy tasks},
  author={Weston, Jason and Bordes, Antoine and Chopra, Sumit and Rush, Alexander M and van Merri{\"e}nboer, Bart and Joulin, Armand and Mikolov, Tomas},
  journal={arXiv preprint arXiv:1502.05698},
  year={2015}
}

@inproceedings{sukhbaatar2015end,
  title={End-to-end memory networks},
  author={Sukhbaatar, Sainbayar and Weston, Jason and Fergus, Rob and others},
  booktitle={Advances in neural information processing systems},
  pages={2440--2448},
  year={2015}
}

@phdthesis{karpathy2016connecting,
  title={Connecting images and natural language},
  author={Karpathy, Andrej},
  year={2016},
  school={Ph. D. thesis, Stanford University}
}

@inproceedings{deng2009imagenet,
  title={Imagenet: A large-scale hierarchical image database},
  author={Deng, Jia and Dong, Wei and Socher, Richard and Li, Li-Jia and Li, Kai and Fei-Fei, Li},
  booktitle={2009 IEEE conference on computer vision and pattern recognition},
  pages={248--255},
  year={2009},
  organization={Ieee}
}

@article{cer2018universal,
  title={Universal sentence encoder},
  author={Cer, Daniel and Yang, Yinfei and Kong, Sheng-yi and Hua, Nan and Limtiaco, Nicole and John, Rhomni St and Constant, Noah and Guajardo-Cespedes, Mario and Yuan, Steve and Tar, Chris and others},
  journal={arXiv preprint arXiv:1803.11175},
  year={2018}
}

@article{howard2018universal,
  title={Universal language model fine-tuning for text classification},
  author={Howard, Jeremy and Ruder, Sebastian},
  journal={arXiv preprint arXiv:1801.06146},
  year={2018}
}

@article{olden2004accurate,
  title={An accurate comparison of methods for quantifying variable importance in artificial neural networks using simulated data},
  author={Olden, Julian D and Joy, Michael K and Death, Russell G},
  journal={Ecological modelling},
  volume={178},
  number={3-4},
  pages={389--397},
  year={2004},
  publisher={Elsevier}
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@inproceedings{heaton2017early,
  title={Early stabilizing feature importance for TensorFlow deep neural networks},
  author={Heaton, Jeff and McElwee, Steven and Fraley, James and Cannady, James},
  booktitle={2017 International Joint Conference on Neural Networks (IJCNN)},
  pages={4618--4624},
  year={2017},
  organization={IEEE}
}

@article{heaton2015encog,
  title={Encog: Library of interchangeable machine learning models for java and c\#},
  author={Heaton, Jeff},
  journal={arXiv preprint arXiv:1506.04776},
  year={2015}
}

@article{heaton2017automated,
  title={Automated Feature Engineering for Deep Neural Networks with Genetic Programming},
  author={Heaton, Jeff T},
  year={2017}
}

@article{heaton2019evolving,
  title={Evolving continuous cellular automata for aesthetic objectives},
  author={Heaton, Jeff},
  journal={Genetic Programming and Evolvable Machines},
  volume={20},
  number={1},
  pages={93--125},
  year={2019},
  publisher={Springer}
}

@article{breiman2001random,
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@inproceedings{ng2004feature,
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@inproceedings{snoek2012practical,
  title={Practical bayesian optimization of machine learning algorithms},
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}

@inproceedings{zhu2021tph,
  title={TPH-YOLOv5: Improved YOLOv5 Based on Transformer Prediction Head for Object Detection on Drone-captured Scenarios},
  author={Zhu, Xingkui and Lyu, Shuchang and Wang, Xu and Zhao, Qi},
  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
  pages={2778--2788},
  year={2021}
}

@article{ashrapov2020tabular,
  title={Tabular GANs for uneven distribution},
  author={Ashrapov, Insaf},
  journal={arXiv preprint arXiv:2010.00638},
  year={2020}
}

@inproceedings{gatys2016image,
  title={Image style transfer using convolutional neural networks},
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  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
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}

@article{simonyan2014very,
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@article{vaswani2017attention,
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  journal={Advances in neural information processing systems},
  volume={30},
  year={2017}
}

@inproceedings{saravia2018carer,
  title={Carer: Contextualized affect representations for emotion recognition},
  author={Saravia, Elvis and Liu, Hsien-Chi Toby and Huang, Yen-Hao and Wu, Junlin and Chen, Yi-Shin},
  booktitle={Proceedings of the 2018 conference on empirical methods in natural language processing},
  pages={3687--3697},
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}

@article{stevens1946theory,
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