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NeuralEF: Deconstructing Kernels by Deep Neural Networks

NeuralEF: Deconstructing Kernels by Deep Neural Networks

30 April 2022
Zhijie Deng
Jiaxin Shi
Jun Zhu
ArXivPDFHTML

Papers citing "NeuralEF: Deconstructing Kernels by Deep Neural Networks"

12 / 12 papers shown
Title
Operator SVD with Neural Networks via Nested Low-Rank Approximation
Operator SVD with Neural Networks via Nested Low-Rank Approximation
Jeonghun Ryu
Xiangxiang Xu
H. Erol
Yuheng Bu
Lizhong Zheng
G. Wornell
21
0
0
06 Feb 2024
Improved Operator Learning by Orthogonal Attention
Improved Operator Learning by Orthogonal Attention
Zipeng Xiao
Zhongkai Hao
Bokai Lin
Zhijie Deng
Hang Su
24
13
0
19 Oct 2023
Contrastive Learning as Kernel Approximation
Contrastive Learning as Kernel Approximation
Konstantinos Christopher Tsiolis
SSL
18
0
0
06 Sep 2023
Representations and Exploration for Deep Reinforcement Learning using
  Singular Value Decomposition
Representations and Exploration for Deep Reinforcement Learning using Singular Value Decomposition
Yash Chandak
S. Thakoor
Z. Guo
Yunhao Tang
Rémi Munos
Will Dabney
Diana Borsa
13
2
0
01 May 2023
Learning Neural Eigenfunctions for Unsupervised Semantic Segmentation
Learning Neural Eigenfunctions for Unsupervised Semantic Segmentation
Zhijie Deng
Yucen Luo
24
6
0
06 Apr 2023
Uni-Fusion: Universal Continuous Mapping
Uni-Fusion: Universal Continuous Mapping
Yijun Yuan
Andreas Nüchter
40
9
0
22 Mar 2023
A Novel Stochastic Gradient Descent Algorithm for Learning Principal
  Subspaces
A Novel Stochastic Gradient Descent Algorithm for Learning Principal Subspaces
Charline Le Lan
Joshua Greaves
Jesse Farebrother
Mark Rowland
Fabian Pedregosa
Rishabh Agarwal
Marc G. Bellemare
44
8
0
08 Dec 2022
Accelerated Linearized Laplace Approximation for Bayesian Deep Learning
Accelerated Linearized Laplace Approximation for Bayesian Deep Learning
Zhijie Deng
Feng Zhou
Jun Zhu
BDL
47
19
0
23 Oct 2022
Neural Eigenfunctions Are Structured Representation Learners
Neural Eigenfunctions Are Structured Representation Learners
Zhijie Deng
Jiaxin Shi
Hao Zhang
Peng Cui
Cewu Lu
Jun Zhu
50
14
0
23 Oct 2022
Contrastive Learning Can Find An Optimal Basis For Approximately
  View-Invariant Functions
Contrastive Learning Can Find An Optimal Basis For Approximately View-Invariant Functions
Daniel D. Johnson
Ayoub El Hanchi
Chris J. Maddison
SSL
24
22
0
04 Oct 2022
Incorporating Prior Knowledge into Neural Networks through an Implicit
  Composite Kernel
Incorporating Prior Knowledge into Neural Networks through an Implicit Composite Kernel
Ziyang Jiang
Tongshu Zheng
Yiling Liu
David Carlson
30
4
0
15 May 2022
Spectral Inference Networks: Unifying Deep and Spectral Learning
Spectral Inference Networks: Unifying Deep and Spectral Learning
David Pfau
Stig Petersen
Ashish Agarwal
David Barrett
Kimberly L. Stachenfeld
51
40
0
06 Jun 2018
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