1. ImageNet: A large-scale hierarchical image database
2. Timur Garipov , Dmitry Podoprikhin , Alexander Novikov , and Dmitry Vetrov . 2016. Ultimate tensorization: compressing convolutional and FC layers alike. arXiv preprint arXiv:1611.03214 ( 2016 ). Timur Garipov, Dmitry Podoprikhin, Alexander Novikov, and Dmitry Vetrov. 2016. Ultimate tensorization: compressing convolutional and FC layers alike. arXiv preprint arXiv:1611.03214 (2016).
3. Patrick Gelß. 2017. The Tensor-Train Format and Its Applications: Modeling and Analysis of Chemical Reaction Networks Catalytic Processes Fluid Flows and Brownian Dynamics. Ph. D. Dissertation. Patrick Gelß. 2017. The Tensor-Train Format and Its Applications: Modeling and Analysis of Chemical Reaction Networks Catalytic Processes Fluid Flows and Brownian Dynamics. Ph. D. Dissertation.
4. Patrick Gelß . 2023. The tensor-train format and its applications. Accessed : January 2, 2023 . Patrick Gelß. 2023. The tensor-train format and its applications. Accessed: January 2, 2023.
5. Song Han , Huizi Mao , and William J. Dally . 2016 . Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization, and Huffman Coding. arXiv preprint arXiv:1510.00149 (2016). arxiv:1510.00149 [cs.CV] Song Han, Huizi Mao, and William J. Dally. 2016. Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization, and Huffman Coding. arXiv preprint arXiv:1510.00149 (2016). arxiv:1510.00149 [cs.CV]