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[1] William Rowan Hamilton,et al. ON QUATERNIONS, OR ON A NEW SYSTEM OF IMAGINARIES IN ALGEBRA , 1847 .
[2] E. Smith. On the Theory of Quaternions , 1969 .
[3] William H. Press,et al. Numerical Recipes 3rd Edition: The Art of Scientific Computing , 2007 .
[4] Yoshua Bengio,et al. Understanding the difficulty of training deep feedforward neural networks , 2010, AISTATS.
[5] Yoshua Bengio,et al. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation , 2014, EMNLP.
[6] Sergey Ioffe,et al. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift , 2015, ICML.
[7] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[8] Michael S. Bernstein,et al. ImageNet Large Scale Visual Recognition Challenge , 2014, International Journal of Computer Vision.
[9] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[10] Alex Graves,et al. Associative Long Short-Term Memory , 2016, ICML.
[11] Stephan J. Garbin,et al. Harmonic Networks: Deep Translation and Rotation Equivariance , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[12] Dmitry P. Vetrov,et al. Variational Dropout Sparsifies Deep Neural Networks , 2017, ICML.
[13] Bo Chen,et al. MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications , 2017, ArXiv.
[14] Richard Socher,et al. Pointer Sentinel Mixture Models , 2016, ICLR.
[15] Max Welling,et al. Learning Sparse Neural Networks through L0 Regularization , 2017, ICLR.
[16] Quoc V. Le,et al. Searching for Activation Functions , 2018, arXiv.
[17] Anthony S. Maida,et al. Deep Quaternion Networks , 2017, 2018 International Joint Conference on Neural Networks (IJCNN).
[18] Michael Carbin,et al. The Lottery Ticket Hypothesis: Training Pruned Neural Networks , 2018, ArXiv.
[19] Ilya Sutskever,et al. Generating Long Sequences with Sparse Transformers , 2019, ArXiv.
[20] Erich Elsen,et al. The State of Sparsity in Deep Neural Networks , 2019, ArXiv.
[21] Yiming Yang,et al. Transformer-XL: Attentive Language Models beyond a Fixed-Length Context , 2019, ACL.
[22] André Stork,et al. Joint Schedule and Layout Autotuning for Sparse Matrices with Compound Entries on GPUs , 2019, VMV.
[23] Xiaoou Tang,et al. Switchable Whitening for Deep Representation Learning , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[24] Lukasz Kaiser,et al. Reformer: The Efficient Transformer , 2020, ICLR.
[25] P. S. Castro,et al. Rigging the Lottery: Making All Tickets Winners , 2019, ICML.
[26] Yao-Hung Hubert Tsai,et al. Complex Transformer: A Framework for Modeling Complex-Valued Sequence , 2019, ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[27] Jiasong Wu,et al. Deep Octonion Networks , 2019, Neurocomputing.
[28] Yee Whye Teh,et al. Multiplicative Interactions and Where to Find Them , 2020, ICLR.
[29] Danilo Comminiello,et al. Compressing deep quaternion neural networks with targeted regularization , 2019, CAAI Trans. Intell. Technol..
[30] Erich Elsen,et al. Fast Sparse ConvNets , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[31] Aurko Roy,et al. Efficient Content-Based Sparse Attention with Routing Transformers , 2020, TACL.