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2205.00165
Cited By
NeuralEF: Deconstructing Kernels by Deep Neural Networks
30 April 2022
Zhijie Deng
Jiaxin Shi
Jun Zhu
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Papers citing
"NeuralEF: Deconstructing Kernels by Deep Neural Networks"
12 / 12 papers shown
Title
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
Zipeng Xiao
Zhongkai Hao
Bokai Lin
Zhijie Deng
Hang Su
24
13
0
19 Oct 2023
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
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
Zhijie Deng
Yucen Luo
24
6
0
06 Apr 2023
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
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
Zhijie Deng
Feng Zhou
Jun Zhu
BDL
47
19
0
23 Oct 2022
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
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
Ziyang Jiang
Tongshu Zheng
Yiling Liu
David Carlson
30
4
0
15 May 2022
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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