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We derive a set of causal deep neural networks whose architectures are a consequence of tensor (multilinear) factor analysis, a framework that facilitates causal inference.
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M. A. O. Vasilescu and D. Terzopoulos · 2002
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Multilinear analysis of image ensembles: TensorFaces
M. A. O. Vasilescu and D. Terzopoulos · 2002
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Recognizing human action efforts: An adaptive three-mode PCA framework
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Facial expression decomposition
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Multilinear subspace analysis of image ensembles
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Speeding-up convolutional neural networks using fine-tuned cp-decomposition
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Deepface: Closing the gap to human-level performance in face verification
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An end-to-end system for unconstrained face verification with deep convolutional neural networks
J. C. Chen, R. Ranjan, A. Kumar, C. H. Chen, V. M. Patel, and R. Chellappa · 2015
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M. A. O. Vasilescu and D. Terzopoulos · 2004
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A primer on kernel methods
J.-P. Vert, K. Tsuda, and B. Schölkopf · 2004
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Bilinear sparse coding for invariant vision
D. B. Grimes and R. P. Rao · 2005
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Multilinear independent components analysis
M. A. O. Vasilescu and D. Terzopoulos · 2005
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Face transfer with multilinear models
D. Vlasic, M. Brand, H. Pfister, and J. Popovic · 2005
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Making things happen: A theory of causal explanation
J. Woodward · 2005
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G. Imbens and D. Rubin · 2015
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Compression of deep convolutional neural networks for fast and low power mobile applications
Y. Kim, E. Park, S. Yoo, T. Choi, L. Yang, and D. Shin · 2015
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Tensorizing neural networks
A. Novikov, D. Podoprikhin, A. Osokin, and D. P. Vetrov · 2015
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Compositional dictionaries for domain adaptive face recognition
Q. Qiu and R. Chellappa · 2015
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Deep learning and the information bottleneck principle
N. Tishby and N. Zaslavsky · 2015
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Disentangling factors of variation in deep representation using adversarial training
M. F. Mathieu, J. J. Zhao, J. Zhao, A. Ramesh, P. Sprechmann, and Y. LeCun · 2016
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Convolutional fusion network for face verification in the wild
C. Xiong, L. Liu, X. Zhao, S. Yan, and T. K. Kim · 2016
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Identifying medical diagnoses and treatable diseases by image-based deep learning
D. S. Kermany, M. Goldbaum, W. Cai, C. C. Valentim, H. Liang, S. L. Baxter, A. McKeown, G. Yang, X. Wu, F. Yan, J. Dong, M. K. Prasadha, J. Pei, M. Y. Ting, J. Zhu, C. Li, S. Hewett, J. Dong, I. Ziyar, A. Shi, R. Zhang, L. Zheng, R. Hou, W. Shi, X. Fu, Y. Duan, V. A. Huu, C. Wen, E. D. Zhang, C. L. Zhang, O. Li, X. Wang, M. A. Singer, X. Sun, J. Xu, A. Tafreshi, M. A. Lewis, H. Xia, and K. Zhang · 2018
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The Mythos of Model Interpretability
Z. C. Lipton · 2018
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Semi-supervised learning with generative adversarial networks for chest x-ray classification with ability of data domain adaptation
A. Madani, M. Moradi, A. Karargyris, and T. Syeda-Mahmood · 2018
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Efficient contraction of large tensor networks for weighted model counting through graph decompositions, 2019
J. M. Dudek, L. Dueñas-Osorio, and M. Y. Vardi · 2019
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Troubling trends in machine learning scholarship: Some ml papers suffer from flaws that could mislead the public and stymie future research
Z. C. Lipton and J. Steinhardt · 2019
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High-performance medicine: the convergence of human and artificial intelligence
E. J. Topol · 2019
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Compositional hierarchical tensor factorization: Representing hierarchical intrinsic and extrinsic causal factors
M. A. O. Vasilescu and E. Kim · 2019
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Incremental multi-domain learning with network latent tensor factorization
A. Bulat, J. Kossaifi, G. Tzimiropoulos, and M. Pantic · 2020
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Geometrical Methods in Machine Learning and Tensor Analysis
V. Khrulkov · 2020
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A fully tensorized recurrent neural network
C. C. Onu, J. E. Miller, and D. Precup · 2020
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Identification of linear and bilinear systems: A unified study
J. Benesty, C. Paleologu, L. Dogariu, and S. Ciochină · 2021
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Multiscale vision transformers
H. Fan, B. Xiong, K. Mangalam, Y. Li, Z. Yan, J. Malik, and C. Feichtenhofer · 2021
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Datasheets for datasets
T. Gebru, J. Morgenstern, B. Vecchione, J. W. Vaughan, H. Wallach, H. Daumé III, and K. Crawford · 2021
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A new approach to multilinear dynamical systems and control, 2021
R. C. Hoover, K. Caudle, and K. Braman · 2021
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Lower memory oblivious (tensor) subspace embeddings with fewer random bits: modewise methods for least squares
M. A. Iwen, D. Needell, E. Rebrova, and A. Zare · 2021
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Swin transformer: Hierarchical vision transformer using shifted windows
Z. Liu, Y. Lin, Y. Cao, H. Hu, Y. Wei, Z. Zhang, S. Lin, and B. Guo · 2021
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CausalX: Causal eXplanations and block multilinear factor analysis
M. A. O. Vasilescu, E. Kim, and X. S. Zeng · 2021
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A generalized hierarchical nonnegative tensor decomposition, 2021
J. Vendrow, J. Haddock, and D. Needell · 2021
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Pyramid vision transformer: A versatile backbone for dense prediction without convolutions
W. Wang, E. Xie, X. Li, D.-P. Fan, K. Song, D. Liang, T. Lu, P. Luo, and L. Shao · 2021
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