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Dynamic neural network is an emerging research topic in deep learning.
Statistical theory of extreme values and some practical applications
Emil Julius Gumbel · 1954
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Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex
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Adaptive mixtures of local experts
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Learning to control fast-weight memories: An alternative to dynamic recurrent networks
Jürgen Schmidhuber · 1992
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Networks of spiking neurons: the third generation of neural network models
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Long short-term memory
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Neural network-based face detection
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Selectivity for the shape, size, and orientation of objects for grasping in neurons of monkey parietal area aip
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Simple model of spiking neurons
Eugene M Izhikevich · 2003
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Robust real-time face detection
Paul Viola and Michael J. Jones · 2004
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Estimating or propagating gradients through stochastic neurons for conditional computation
Yoshua Bengio, Nicholas Léonard, and Aaron Courville · 2013
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Low-rank approximations for conditional feedforward computation in deep neural networks
Andrew Davis and Itamar Arel · 2013
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Learning factored representations in a deep mixture of experts
David Eigen, Marc’Aurelio Ranzato, and Ilya Sutskever · 2013
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Predicting parameters in deep learning
Misha Denil, Babak Shakibi, Laurent Dinh, Marc’Aurelio Ranzato, and Nando De Freitas · 2013
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Deep convolutional network cascade for facial point detection
Yi Sun, Xiaogang Wang, and Xiaoou Tang · 2013
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Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean · 2014
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Speeding up convolutional neural networks with low rank expansions
Max Jaderberg, Andrea Vedaldi, and Andrew Zisserman · 2014
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Kyunghyun Cho and Yoshua Bengio · 2014
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Neural decision forests for semantic image labelling
Samuel Rota Bulo and Peter Kontschieder · 2014
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Recurrent models of visual attention
Volodymyr Mnih, Nicolas Heess, and Alex Graves · 2014
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2015
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Going deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2015
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
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Big/little deep neural network for ultra low power inference
Eunhyeok Park, Dongyoung Kim, Soobeom Kim, Yong-Deok Kim, Gunhee Kim, Sungroh Yoon, and Sungjoo Yoo · 2015
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Deep neural decision forests
Peter Kontschieder, Madalina Fiterau, Antonio Criminisi, and Samuel Rota Bulo · 2015
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Hd-cnn: hierarchical deep convolutional neural networks for large scale visual recognition
Zhicheng Yan, Hao Zhang, Robinson Piramuthu, Vignesh Jagadeesh, Dennis DeCoste, Wei Di, and Yizhou Yu · 2015
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Spatial transformer networks
Max Jaderberg, Karen Simonyan, and Andrew Zisserman · 2015
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A convolutional neural network cascade for face detection
Haoxiang Li, Zhe Lin, Xiaohui Shen, Jonathan Brandt, and Gang Hua · 2015
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Real-Time Pedestrian Detection with Deep Network Cascades
Anelia Angelova, Alex Krizhevsky, Vincent Vanhoucke, Abhijit Ogale, and Dave Ferguson · 2015
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Conditioned regression models for non-blind single image super-resolution
Gernot Riegler, Samuel Schulter, Matthias Ruther, and Horst Bischof · 2015
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The application of two-level attention models in deep convolutional neural network for fine-grained image classification
Tianjun Xiao, Yichong Xu, Kuiyuan Yang, Jiaxing Zhang, Yuxin Peng, and Zheng Zhang · 2015
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Multiple object recognition with visual attention
Jimmy Ba, Volodymyr Mnih, and Koray Kavukcuoglu · 2015
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Show, attend and tell: Neural image caption generation with visual attention
Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron Courville, Ruslan Salakhudinov, Rich Zemel, and Yoshua Bengio · 2015
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Learning spatiotemporal features with 3d convolutional networks
Du Tran, Lubomir Bourdev, Rob Fergus, Lorenzo Torresani, and Manohar Paluri · 2015
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Adaptive computation time for recurrent neural networks
Alex Graves · 2016
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Learning feed-forward one-shot learners
Luca Bertinetto, João F Henriques, Jack Valmadre, Philip HS Torr, and Andrea Vedaldi · 2016
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Binarized neural networks
Itay Hubara, Matthieu Courbariaux, Daniel Soudry, Ran El-Yaniv, and Yoshua Bengio · 2016
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Branchynet: Fast inference via early exiting from deep neural networks
Surat Teerapittayanon, Bradley McDanel, and Hsiang-Tsung Kung · 2016
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Conditional computation in neural networks for faster models
Emmanuel Bengio, Pierre-Luc Bacon, Joelle Pineau, and Doina Precup · 2016
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Decision forests, convolutional networks and the models in-between
Yani Ioannou, Duncan Robertson, Darko Zikic, Peter Kontschieder, Jamie Shotton, Matthew Brown, and Antonio Criminisi · 2016
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Dynamic filter networks
Xu Jia, Bert De Brabandere, Tinne Tuytelaars, and Luc V Gool · 2016
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Hypernetworks
David Ha, Andrew Dai, and Quoc V Le · 2016
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Learning deep features for discriminative localization
Bolei Zhou, Aditya Khosla, Agata Lapedriza, Aude Oliva, and Antonio Torralba · 2016
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Dynamic capacity networks
Amjad Almahairi, Nicolas Ballas, Tim Cooijmans, Yin Zheng, Hugo Larochelle, and Aaron Courville · 2016
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Visual concept recognition and localization via iterative introspection
Amir Rosenfeld and Shimon Ullman · 2016
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End-to-end learning of action detection from frame glimpses in videos
Serena Yeung, Olga Russakovsky, Greg Mori, and Li Fei-Fei · 2016
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Leaving some stones unturned: dynamic feature prioritization for activity detection in streaming video
Yu-Chuan Su and Kristen Grauman · 2016
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Exploit all the layers: Fast and accurate cnn object detector with scale dependent pooling and cascaded rejection classifiers
Fan Yang, Wongun Choi, and Yuanqing Lin · 2016
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Attend, infer, repeat: Fast scene understanding with generative models
SM Ali Eslami, Nicolas Heess, Theophane Weber, Yuval Tassa, David Szepesvari, and Geoffrey E. Hinton · 2016
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Cnvlutin: Ineffectual-Neuron-Free Deep Neural Network Computing
Jorge Albericio, Patrick Judd, Tayler Hetherington, Tor Aamodt, Natalie Enright Jerger, and Andreas Moshovos · 2016
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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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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Neural architecture search with reinforcement learning
Barret Zoph and Quoc V Le · 2017
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Dynamic routing between capsules
Sara Sabour, Nicholas Frosst, and Geoffrey E Hinton · 2017
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Runtime neural pruning
Ji Lin, Yongming Rao, Jiwen Lu, and Jie Zhou · 2017
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Outrageously large neural networks: The sparsely-gated mixture-of-experts layer
Noam Shazeer, Azalia Mirhoseini, Krzysztof Maziarz, Andy Davis, Quoc Le, Geoffrey Hinton, and Jeff Dean · 2017
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Neural aggregation network for video face recognition
Jiaolong Yang, Peiran Ren, Dongqing Zhang, Dong Chen, Fang Wen, Hongdong Li, and Gang Hua · 2017
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Mobilenets: Efficient convolutional neural networks for mobile vision applications
Andrew G Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, Tobias Weyand, Marco Andreetto, and Hartwig Adam · 2017
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Spatially adaptive computation time for residual networks
Michael Figurnov, Maxwell D Collins, Yukun Zhu, Li Zhang, Jonathan Huang, Dmitry Vetrov, and Ruslan Salakhutdinov · 2017
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Not all pixels are equal: Difficulty-aware semantic segmentation via deep layer cascade
Xiaoxiao Li, Ziwei Liu, Ping Luo, Chen Change Loy, and Xiaoou Tang · 2017
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Learning efficient convolutional networks through network slimming
Zhuang Liu, Jianguo Li, Zhiqiang Shen, Gao Huang, Shoumeng Yan, and Changshui Zhang · 2017
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Adaptive neural networks for efficient inference
Tolga Bolukbasi, Joseph Wang, Ofer Dekel, and Venkatesh Saligrama · 2017
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Idk cascades: Fast deep learning by learning not to overthink
Xin Wang, Yujia Luo, Daniel Crankshaw, Alexey Tumanov, Fisher Yu, and Joseph E Gonzalez · 2017
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The cascading neural network: building the internet of smart things
Sam Leroux, Steven Bohez, Elias De Coninck, Tim Verbelen, Bert Vankeirsbilck, Pieter Simoens, and Bart Dhoedt · 2017
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Deciding how to decide: Dynamic routing in artificial neural networks
Mason McGill and Pietro Perona · 2017
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Reasonet: Learning to stop reading in machine comprehension
Yelong Shen, Po-Sen Huang, Jianfeng Gao, and Weizhu Chen · 2017
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Changing model behavior at test-time using reinforcement learning
Augustus Odena, Dieterich Lawson, and Christopher Olah · 2017
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Distilling a neural network into a soft decision tree
Nicholas Frosst and Geoffrey Hinton · 2017
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Segmentation-aware convolutional networks using local attention masks
Adam W. Harley, Konstantinos G. Derpanis, and Iasonas Kokkinos · 2017
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Deformable convolutional networks
Jifeng Dai, Haozhi Qi, Yuwen Xiong, Yi Li, Guodong Zhang, Han Hu, and Yichen Wei · 2017
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Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs
Martin Simonovsky and Nikos Komodakis · 2017
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Incorporating side information by adaptive convolution
Di Kang, Debarun Dhar, and Antoni Chan · 2017
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Modulating early visual processing by language
Harm de Vries, Florian Strub, Jérémie Mary, Hugo Larochelle, Olivier Pietquin, and Aaron Courville · 2017
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Residual attention network for image classification
Fei Wang, Mengqing Jiang, Chen Qian, Shuo Yang, Cheng Li, Honggang Zhang, Xiaogang Wang, and Xiaoou Tang · 2017
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Sca-cnn: Spatial and channel-wise attention in convolutional networks for image captioning
Long Chen, Hanwang Zhang, Jun Xiao, Liqiang Nie, Jian Shao, Wei Liu, and Tat-Seng Chua · 2017
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Autoscaler: Scale-attention networks for visual correspondence
Shenlong Wang, Linjie Luo, Ning Zhang, and Li-Jia Li · 2017
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More is less: A more complicated network with less inference complexity
Xuanyi Dong, Junshi Huang, Yi Yang, and Shuicheng Yan · 2017
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Training-free, single-image super-resolution using a dynamic convolutional network
Aritra Bhowmik, Suprosanna Shit, and Chandra Sekhar Seelamantula · 2017
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Dynamic computational time for visual attention
Zhichao Li, Yi Yang, Xiao Liu, Feng Zhou, Shilei Wen, and Wei Xu · 2017
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Look closer to see better: Recurrent attention convolutional neural network for fine-grained image recognition
Jianlong Fu, Heliang Zheng, and Tao Mei · 2017
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Scale-aware face detection
Zekun Hao, Yu Liu, Hongwei Qin, Junjie Yan, Xiu Li, and Xiaolin Hu · 2017
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Variable computation in recurrent neural networks
Yacine Jernite, Edouard Grave, Armand Joulin, and Tomas Mikolov · 2017
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Hierarchical multiscale recurrent neural networks
Junyoung Chung, Sungjin Ahn, and Yoshua Bengio · 2017
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Length adaptive recurrent model for text classification
Zhengjie Huang, Zi Ye, Shuangyin Li, and Rong Pan · 2017
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Learning to Skim Text
Adams Wei Yu, Hongrae Lee, and Quoc Le · 2017
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Attention-aware deep reinforcement learning for video face recognition
Yongming Rao, Jiwen Lu, and Jie Zhou · 2017
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On calibration of modern neural networks
Chuan Guo, Geoff Pleiss, Yu Sun, and Kilian Q Weinberger · 2017
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Adaptive feeding: Achieving fast and accurate detections by adaptively combining object detectors
Hong-Yu Zhou, Bin-Bin Gao, and Jianxin Wu · 2017
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Learning multi-attention convolutional neural network for fine-grained image recognition
Heliang Zheng, Jianlong Fu, Tao Mei, and Jiebo Luo · 2017
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Video frame interpolation via adaptive separable convolution
Simon Niklaus, Long Mai, and Feng Liu · 2017
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Video frame interpolation via adaptive convolution
Simon Niklaus, Long Mai, and Feng Liu · 2017
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Online video deblurring via dynamic temporal blending network
Tae Hyun Kim, Kyoung Mu Lee, Bernhard Scholkopf, and Michael Hirsch · 2017
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Attention-based multimodal fusion for video description
Chiori Hori, Takaaki Hori, Teng-Yok Lee, Ziming Zhang, Bret Harsham, John R Hershey, Tim K Marks, and Kazuhiko Sumi · 2017
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Position-based content attention for time series forecasting with sequence-to-sequence rnns
Yagmur Gizem Cinar, Hamid Mirisaee, Parantapa Goswami, Eric Gaussier, Ali Aït-Bachir, and Vadim Strijov · 2017
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Categorical reparameterization with gumbel-softmax
Eric Jang, Shixiang Gu, and Ben Poole · 2017
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Quo vadis, action recognition? a new model and the kinetics dataset
Spatio-temporal filter adaptive network for video deblurring
Shangchen Zhou, Jiawei Zhang, Jinshan Pan, Haozhe Xie, Wangmeng Zuo, and Jimmy Ren · 2019
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Kpconv: Flexible and deformable convolution for point clouds
Hugues Thomas, Charles R. Qi, Jean-Emmanuel Deschaud, Beatriz Marcotegui, François Goulette, and Leonidas J. Guibas · 2019
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Videobert: A joint model for video and language representation learning
Chen Sun, Austin Myers, Carl Vondrick, Kevin Murphy, and Cordelia Schmid · 2019
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Multi-horizon time series forecasting with temporal attention learning
Chenyou Fan, Yuze Zhang, Yi Pan, Xiaoyue Li, Chi Zhang, Rong Yuan, Di Wu, Wensheng Wang, Jian Pei, and Heng Huang · 2019
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Adaptive convolution for multi-relational learning
Xiaotian Jiang, Quan Wang, and Bin Wang · 2019
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Session-based social recommendation via dynamic graph attention networks
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Joao Carreira and Andrew Zisserman · 2017
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Predictivenet: An energy-efficient convolutional neural network via zero prediction
Yingyan Lin, Charbel Sakr, Yongjune Kim, and Naresh Shanbhag · 2017
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DARTS: Differentiable Architecture Search
Hanxiao Liu, Karen Simonyan, and Yiming Yang · 2018
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Multi-scale dense networks for resource efficient image classification
Gao Huang, Danlu Chen, Tianhong Li, Felix Wu, Laurens van der Maaten, and Kilian Weinberger · 2018
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Squeeze-and-excitation networks
Jie Hu, Li Shen, and Gang Sun · 2018
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Cbam: Convolutional block attention module
Sanghyun Woo, Jongchan Park, Joon-Young Lee, and In So Kweon · 2018
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Condensenet: An efficient densenet using learned group convolutions
Gao Huang, Shichen Liu, Laurens Van der Maaten, and Kilian Q Weinberger · 2018
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Weiping Song, Zhiping Xiao, Yifan Wang, Laurent Charlin, Ming Zhang, and Jian Tang · 2019
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Autoint: Automatic feature interaction learning via self-attentive neural networks
Weiping Song, Chence Shi, Zhiping Xiao, Zhijian Duan, Yewen Xu, Ming Zhang, and Jian Tang · 2019
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Laf-net: Locally adaptive fusion networks for stereo confidence estimation
Sunok Kim, Seungryong Kim, Dongbo Min, and Kwanghoon Sohn · 2019
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Stnet: Local and global spatial-temporal modeling for action recognition
Dongliang He, Zhichao Zhou, Chuang Gan, Fu Li, Xiao Liu, Yandong Li, Limin Wang, and Shilei Wen · 2019
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Shallow-deep networks: Understanding and mitigating network overthinking
Yigitcan Kaya, Sanghyun Hong, and Tudor Dumitras · 2019
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Spottune: Transfer learning through adaptive fine-tuning
Yunhui Guo, Honghui Shi, Abhishek Kumar, Kristen Grauman, Tajana Rosing, and Rogerio Feris · 2019
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Synetgy: Algorithm-hardware co-design for convnet accelerators on embedded fpgas
Yifan Yang, Qijing Huang, Bichen Wu, Tianjun Zhang, Liang Ma, Giulio Gambardella, Michaela Blott, Luciano Lavagno, Kees Vissers, John Wawrzynek, et al · 2019
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Boosting the performance of cnn accelerators with dynamic fine-grained channel gating
Weizhe Hua, Yuan Zhou, Christopher De Sa, Zhiru Zhang, and G Edward Suh · 2019
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Hardware-software co-design approach for deep learning inference
Debdeep Paul, Jawar Singh, and Jimson Mathew · 2019
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Language models are few-shot learners
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Dynamic convolution: Attention over convolution kernels
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Resolution Adaptive Networks for Efficient Inference
Le Yang, Yizeng Han, Xi Chen, Shiji Song, Jifeng Dai, and Gao Huang · 2020
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Depth-Adaptive Transformer
Maha Elbayad, Jiatao Gu, Edouard Grave, and Michael Auli · 2020
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Glance and focus: a dynamic approach to reducing spatial redundancy in image classification
Yulin Wang, Kangchen Lv, Rui Huang, Shiji Song, Le Yang, and Gao Huang · 2020
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Epnet: Learning to exit with flexible multi-branch network
Xin Dai, Xiangnan Kong, and Tian Guo · 2020
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FastBERT: a Self-distilling BERT with Adaptive Inference Time
Weijie Liu, Peng Zhou, Zhiruo Wang, Zhe Zhao, Haotang Deng, and QI JU · 2020
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DeeBERT: Dynamic Early Exiting for Accelerating BERT Inference
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The Right Tool for the Job: Matching Model and Instance Complexities
Roy Schwartz, Gabriel Stanovsky, Swabha Swayamdipta, Jesse Dodge, and Noah A. Smith · 2020
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BERT Loses Patience: Fast and Robust Inference with Early Exit
Wangchunshu Zhou, Canwen Xu, Tao Ge, Julian McAuley, Ke Xu, and Furu Wei · 2020
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Dynamic Inference: A New Approach Toward Efficient Video Action Recognition
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Finding decision jumps in text classification
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Adabits: Neural network quantization with adaptive bit-widths
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Fractional skipping: Towards finer-grained dynamic cnn inference
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Deep mixture of experts via shallow embedding
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S2dnas: Transforming static cnn model for dynamic inference via neural architecture search
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Channel selection using gumbel softmax
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Batch-shaping for learning conditional channel gated networks
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Dual dynamic inference: Enabling more efficient, adaptive and controllable deep inference
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Dynamic channel and layer gating in convolutional neural networks
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The tree ensemble layer: Differentiability meets conditional computation
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Instanas: Instance-aware neural architecture search
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Learning Dynamic Routing for Semantic Segmentation
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Meta-neighborhoods
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WeightNet: Revisiting the Design Space of Weight Networks
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ECA-net: Efficient channel attention for deep convolutional neural networks
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Spanet: Spatial Pyramid Attention Network for Enhanced Image Recognition
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Dynamic relu
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Funnel activation for visual recognition
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Dynamic Convolutions: Exploiting Spatial Sparsity for Faster Inference
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Spatially Adaptive Inference with Stochastic Feature Sampling and Interpolation
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Pointrend: Image segmentation as rendering
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Dynamic Sampling Networks for Efficient Action Recognition in Videos
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Model rubik’s cube: Twisting resolution, depth and width for tinynets
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Rubiksnet: Learnable 3d-shift for efficient video action recognition
Linxi Fan, Shyamal Buch, Guanzhi Wang, Ryan Cao, Yuke Zhu, Juan Carlos Niebles, and Li Fei-Fei · 2020
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Ar-net: Adaptive frame resolution for efficient action recognition
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Deep multimodal fusion by channel exchanging
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Learning layer-skippable inference network
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Dynamic attention network for semantic segmentation
Fei Wu, Feng Chen, Xiao-Yuan Jing, Chang-Hui Hu, Qi Ge, and Yimu Ji · 2020
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Squeeze-and-Attention Networks for Semantic Segmentation
Zilong Zhong, Zhong Qiu Lin, Rene Bidart, Xiaodan Hu, Ibrahim Ben Daya, Zhifeng Li, Wei-Shi Zheng, Jonathan Li, and Alexander Wong · 2020
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SEAN: Image Synthesis with Semantic Region-Adaptive Normalization
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Spatial-adaptive network for single image denoising
Meng Chang, Qi Li, Huajun Feng, and Zhihai Xu · 2020
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Learned image downscaling for upscaling using content adaptive resampler
Wanjie Sun and Zhenzhong Chen · 2020
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Listen to look: Action recognition by previewing audio
Ruohan Gao, Tae-Hyun Oh, Kristen Grauman, and Lorenzo Torresani · 2020
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Anisotropic convolutional networks for 3d semantic scene completion
Jie Li, Kai Han, Peng Wang, Yu Liu, and Xia Yuan · 2020
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Integrating multimodal information in large pretrained transformers
Wasifur Rahman, Md Kamrul Hasan, Sangwu Lee, Amir Zadeh, Chengfeng Mao, Louis-Philippe Morency, and Ehsan Hoque · 2020
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An efficient group recommendation model with multiattention-based neural networks
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