Fetching the paper…
Reading the bibliography…
The majority of signal data captured in the real world uses numerous sensors with different resolutions.
On the functions which are represented by the expansion of interpolating theory
ET Whittaker · 1915
Earlier work this paper cites.
On the cardinal function of interpolation theory
John Macnaughten Whittaker · 1927
Earlier work this paper cites.
Communication in the presence of noise
Claude E Shannon · 1949
Earlier work this paper cites.
Sampling and reconstruction of wave-number-limited functions in n-dimensional euclidean spaces
Daniel P. Petersen and David Middleton · 1962
Earlier work this paper cites.
An algorithm for the machine calculation of complex fourier series
James W Cooley and John W Tukey · 1965
Earlier work this paper cites.
The laplacian pyramid as a compact image code
Peter J Burt and Edward H Adelson · 1987
Earlier work this paper cites.
Learning multiple layers of features from tiny images
Alex Krizhevsky, Geoffrey Hinton, et al · 2009
Earlier work this paper cites.
An analysis of single-layer networks in unsupervised feature learning
Adam Coates, Andrew Ng, and Honglak Lee · 2011
Earlier work this paper cites.
Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
Earlier work this paper cites.
Tiny imagenet visual recognition challenge
Ya Le and Xuan Yang · 2015
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Deep networks with stochastic depth
Gao Huang, Yu Sun, Zhuang Liu, Daniel Sedra, and Kilian Q Weinberger · 2016
Earlier work this paper cites.
Sgdr: Stochastic gradient descent with warm restarts
Ilya Loshchilov and Frank Hutter · 2016
Cited alongside, same era.
Sergey Zagoruyko and Nikos Komodakis · 2016
Cited alongside, same era.
Deep laplacian pyramid networks for fast and accurate super-resolution
Wei-Sheng Lai, Jia-Bin Huang, Narendra Ahuja, and Ming-Hsuan Yang · 2017
Cited alongside, same era.
Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2017
Cited alongside, same era.
Sigmoid-weighted linear units for neural network function approximation in reinforcement learning
Stefan Elfwing, Eiji Uchibe, and Kenji Doya · 2018
Cited alongside, same era.
Learning continuous image representation with local implicit image function
Yinbo Chen, Sifei Liu, and Xiaolong Wang · 2021
Later among the works it cites.
Neural operator: Learning maps between function spaces
Nikola Kovachki, Zongyi Li, Burigede Liu, Kamyar Azizzadenesheli, Kaushik Bhattacharya, Andrew Stuart, and Anima Anandkumar · 2021
Later among the works it cites.
Nerf: Representing scenes as neural radiance fields for view synthesis
Ben Mildenhall, Pratul P Srinivasan, Matthew Tancik, Jonathan T Barron, Ravi Ramamoorthi, and Ren Ng · 2021
Later among the works it cites.
Trivialaugment: Tuning-free yet state-of-the-art data augmentation
Samuel G Müller and Frank Hutter · 2021
Later among the works it cites.
Frequency disentangled residual network
Satya Rajendra Singh, Roshan Reddy Yedla, Shiv Ram Dubey, Rakesh Sanodiya, and Wei-Ta Chu · 2021
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Mobilenetv2: Inverted residuals and linear bottlenecks
Mark Sandler, Andrew Howard, Menglong Zhu, Andrey Zhmoginov, and Liang-Chieh Chen · 2018
Cited alongside, same era.
Searching for mobilenetv3
Andrew Howard, Mark Sandler, Grace Chu, Liang-Chieh Chen, Bo Chen, Mingxing Tan, Weijun Wang, Yukun Zhu, Ruoming Pang, Vijay Vasudevan, et al · 2019
Cited alongside, same era.
Occupancy networks: Learning 3d reconstruction in function space
Lars Mescheder, Michael Oechsle, Michael Niemeyer, Sebastian Nowozin, and Andreas Geiger · 2019
Cited alongside, same era.
Deepsdf: Learning continuous signed distance functions for shape representation
Jeong Joon Park, Peter Florence, Julian Straub, Richard Newcombe, and Steven Lovegrove · 2019
Cited alongside, same era.
Fourier neural operator for parametric partial differential equations
Zongyi Li, Nikola Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Kaushik Bhattacharya, Andrew Stuart, and Anima Anandkumar · 2020
Cited alongside, same era.
Implicit neural representations with periodic activation functions
Vincent Sitzmann, Julien Martel, Alexander Bergman, David Lindell, and Gordon Wetzstein · 2020
Cited alongside, same era.
Efficientnetv2: Smaller models and faster training
Mingxing Tan and Quoc Le · 2021
Later among the works it cites.
Implicit transformer network for screen content image continuous super-resolution
Jingyu Yang, Sheng Shen, Huanjing Yue, and Kun Li · 2021
Later among the works it cites.
Vladimir Fanaskov and Ivan Oseledets · 2022
Later among the works it cites.
Local texture estimator for implicit representation function
Jaewon Lee and Kyong Hwan Jin · 2022
Later among the works it cites.
Signal processing for implicit neural representations
Dejia Xu, Peihao Wang, Yifan Jiang, Zhiwen Fan, and Zhangyang Wang · 2022
Later among the works it cites.
Representation equivalent neural operators: a framework for alias-free operator learning
Francesca Bartolucci, Emmanuel de Bezenac, Bogdan Raonic, Roberto Molinaro, Siddhartha Mishra, and Rima Alaifari · 2023
Later among the works it cites.