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Thanks to their improved data efficiency, equivariant neural networks have gained increased interest in the deep learning community.
U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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Group Equivariant Convolutional Networks
Taco S. Cohen and Max Welling · 2016
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Exploiting cyclic symmetry in convolutional neural networks
Sander Dieleman, Jeffrey De Fauw, and Koray Kavukcuoglu · 2016
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Deep convolutional neural networks for microscopy-based point of care diagnostics
John A Quinn, Rose Nakasi, Pius K. B. Mugagga, Patrick Byanyima, William Lubega, and Alfred Andama · 2016
Earlier work this paper cites.
Are very deep neural networks feasible on mobile devices
Swati Rallapalli, Hang Qiu, Archith John Bency, S. Karthikeyan, Ramesh Govindan, B. S. Manjunath, and Rahul Urgaonkar · 2016
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Dorefa-net: Training low bitwidth convolutional neural networks with low bitwidth gradients
Shuchang Zhou, Yuxin Wu, Zekun Ni, Xinyu Zhou, He Wen, and Yuheng Zou · 2016
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Steerable CNNs
Taco S. Cohen and Max Welling · 2017
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Densely connected convolutional networks
Gao Huang, Zhuang Liu, Laurens Van Der Maaten, and Kilian Q. Weinberger · 2017
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Quantization and training of neural networks for efficient integer-arithmetic-only inference
Benoit Jacob, Skirmantas Kligys, Bo Chen, Menglong Zhu, Matthew Tang, Andrew G. Howard, Hartwig Adam, and Dmitry Kalenichenko · 2017
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Soft weight-sharing for neural network compression, 2017
Karen Ullrich, Edward Meeds, and Max Welling · 2017
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Harmonic networks: Deep translation and rotation equivariance
Daniel E. Worrall, Stephan J. Garbin, Daniyar Turmukhambetov, and Gabriel J. Brostow · 2017
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Roto-translation covariant convolutional networks for medical image analysis
Erik J. Bekkers, Maxime W Lafarge, Mitko Veta, Koen A.J. Eppenhof, Josien P.W. Pluim, and Remco Duits · 2018
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Machine learning for the developing world
Maria De-Arteaga, William Herlands, Daniel B. Neill, and Artur Dubrawski · 2018
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HexaConv
Emiel Hoogeboom, Jorn W. T. Peters, Taco S. Cohen, and Max Welling · 2018
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On the generalization of equivariance and convolution in neural networks to the action of compact groups
Risi Kondor and Shubhendu Trivedi · 2018
Cited alongside, same era.
Quantizing deep convolutional networks for efficient inference: A whitepaper
Raghuraman Krishnamoorthi · 2018
Cited alongside, same era.
Deeply supervised rotation equivariant network for lesion segmentation in dermoscopy images
Xiaomeng Li, Lequan Yu, Chi-Wing Fu, and Pheng-Ann Heng · 2018
Cited alongside, same era.
Sample efficient semantic segmentation using rotation equivariant convolutional networks
Jasper Linmans, Jim Winkens, Bastiaan S. Veeling, Taco S. Cohen, and Max Welling · 2018
Cited alongside, same era.
Relaxed quantization for discretized neural networks
Christos Louizos, Matthias Reisser, Tijmen Blankevoort, Efstratios Gavves, and Max Welling · 2018
Enhanced Rotation-Equivariant U-Net for Nuclear Segmentation
Benjamin Chidester, That-Vinh Ton, Minh-Triet Tran, Jian Ma, and Minh N. Do · 2019
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A general theory of equivariant cnns on homogeneous spaces
Taco S. Cohen, Mario Geiger, and Maurice Weiler · 2019
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Searching for MobileNetV3
Andrew Howard, Mark Sandler, Grace Chu, Liang-Chieh Chen, Bo Chen, Mingxing Tan, Weijun Wang, Yukun Zhu, Ruoming Pang, Vijay Vasudevan, Quoc V. Le, and Hartwig Adam · 2019
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Taxonomy and evaluation of structured compression of convolutional neural networks, 2019
Andrey Kuzmin, Markus Nagel, Saurabh Pitre, Sandeep Pendyam, Tijmen Blankevoort, and Max Welling · 2019
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Deep-learning-based aerial image classification for emergency response applications using unmanned aerial vehicles
Christos Kyrkou and Theocharis Theocharides · 2019
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Cited alongside, same era.
MobileNetV2: Inverted Residuals and Linear Bottlenecks
Mark Sandler, Andrew Howard, Menglong Zhu, Andrey Zhmoginov, and Liang Chieh Chen · 2018
Cited alongside, same era.
A quantization-friendly separable convolution for mobilenets
Tao Sheng, Chen Feng, Shaojie Zhuo, Xiaopeng Zhang, Liang Shen, and Mickey Aleksic · 2018
Cited alongside, same era.
Rotation equivariant CNNs for digital pathology
Bastiaan S Veeling, Jasper Linmans, Jim Winkens, Taco Cohen, and Max Welling · 2018
Cited alongside, same era.
Artificial intelligence (ai) and global health: how can ai contribute to health in resource-poor settings?
Brian Wahl, Aline Cossy-Gantner, Stefan Germann, and Nina R Schwalbe · 2018
Cited alongside, same era.
Learning steerable filters for rotation equivariant CNNs
Maurice Weiler, Fred A. Hamprecht, and Martin Storath · 2018
Cited alongside, same era.
3D G-CNNs for pulmonary nodule detection
Marysia Winkels and Taco S. Cohen · 2018
Cited alongside, same era.
ProxylessNAS: Direct neural architecture search on target task and hardware
Han Cai, Ligeng Zhu, and Song Han · 2019
Cited alongside, same era.
Same, same but different: Recovering neural network quantization error through weight factorization
Eldad Meller, Alexander Finkelstein, Uri Almog, and Mark Grobman · 2019
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Data-Free Quantization through Weight Equalization and Bias Correction
Markus Nagel, Mart van Baalen, Tijmen Blankevoort, and Max Welling · 2019
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Quantized deep learning models on low-power edge devices for robotic systems, 2019
Anugraha Sinha, Naveen Kumar, Murukesh Mohanan, MD Muhaimin Rahman, Yves Quemener, Amina Mim, and Suzana Ilić · 2019
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EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
Mingxing Tan and Quoc V. Le · 2019
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General E ( 2 ) E(2) -Equivariant Steerable CNNs
Maurice Weiler and Gabriele Cesa · 2019
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Deep scale-spaces: Equivariance over scale
Daniel E. Worrall and Max Welling · 2019
Later among the works it cites.
B-spline CNNs on lie groups
Erik J Bekkers · 2020
Closest in time.
Zeroq: A novel zero shot quantization framework, 2020
Yaohui Cai, Zhewei Yao, Zhen Dong, Amir Gholami, Michael W. Mahoney, and Kurt Keutzer · 2020
Closest in time.
Attentive group equivariant convolutional networks
David W Romero, Erik J Bekkers, Jakub M Tomczak, and Mark Hoogendoorn · 2020
Closest in time.