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Growing Cosine Unit: A Novel Oscillatory Activation Function That Can Speedup Training and Reduce Parameters in Convolutional Neural Networks
30 August 2021
M. M. Noel
L. Arunkumar
A. Trivedi
Praneet Dutta
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Papers citing
"Growing Cosine Unit: A Novel Oscillatory Activation Function That Can Speedup Training and Reduce Parameters in Convolutional Neural Networks"
8 / 8 papers shown
Title
PReLU: Yet Another Single-Layer Solution to the XOR Problem
Rafael C. Pinto
Anderson R. Tavares
22
1
0
17 Sep 2024
Modeling non-linear Effects with Neural Networks in Relational Event Models
Edoardo Filippi-Mazzola
Ernst C. Wit
24
1
0
19 Dec 2023
Efficient Vectorized Backpropagation Algorithms for Training Feedforward Networks Composed of Quadratic Neurons
M. M. Noel
Venkataraman Muthiah-Nakarajan
Yug Oswal
28
0
0
04 Oct 2023
Embeddings between Barron spaces with higher order activation functions
T. J. Heeringa
L. Spek
Felix L. Schwenninger
C. Brune
37
3
0
25 May 2023
Amplifying Sine Unit: An Oscillatory Activation Function for Deep Neural Networks to Recover Nonlinear Oscillations Efficiently
J. Rahman
Faiza Makhdoom
D. Lu
27
7
0
18 Apr 2023
Evaluating CNN with Oscillatory Activation Function
Jeevanshi Sharma
13
1
0
13 Nov 2022
Sample-based Uncertainty Quantification with a Single Deterministic Neural Network
T. Kanazawa
Chetan Gupta
UQCV
30
4
0
17 Sep 2022
How important are activation functions in regression and classification? A survey, performance comparison, and future directions
Ameya Dilip Jagtap
George Karniadakis
AI4CE
37
71
0
06 Sep 2022
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