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SPADE4: Sparsity and Delay Embedding based Forecasting of Epidemics

SPADE4: Sparsity and Delay Embedding based Forecasting of Epidemics

11 November 2022
Esha Saha
L. Ho
Giang Tran
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Papers citing "SPADE4: Sparsity and Delay Embedding based Forecasting of Epidemics"

14 / 14 papers shown
Title
SRMD: Sparse Random Mode Decomposition
SRMD: Sparse Random Mode Decomposition
Nicholas Richardson
Hayden Schaeffer
Giang Tran
40
11
0
12 Apr 2022
Parameter Inference of Time Series by Delay Embeddings and Learning
  Differentiable Operators
Parameter Inference of Time Series by Delay Embeddings and Learning Differentiable Operators
A. Lin
Adrian S. Wong
R. Martin
Stanley J. Osher
D. Eckhardt
AI4TS
43
2
0
11 Mar 2022
HARFE: Hard-Ridge Random Feature Expansion
HARFE: Hard-Ridge Random Feature Expansion
Esha Saha
Hayden Schaeffer
Giang Tran
96
15
0
06 Feb 2022
Discovery of Nonlinear Dynamical Systems using a Runge-Kutta Inspired
  Dictionary-based Sparse Regression Approach
Discovery of Nonlinear Dynamical Systems using a Runge-Kutta Inspired Dictionary-based Sparse Regression Approach
P. Goyal
P. Benner
56
49
0
11 May 2021
Fourier Neural Operator for Parametric Partial Differential Equations
Fourier Neural Operator for Parametric Partial Differential Equations
Zong-Yi Li
Nikola B. Kovachki
Kamyar Azizzadenesheli
Burigede Liu
K. Bhattacharya
Andrew M. Stuart
Anima Anandkumar
AI4CE
494
2,401
0
18 Oct 2020
Implicit Neural Representations with Periodic Activation Functions
Implicit Neural Representations with Periodic Activation Functions
Vincent Sitzmann
Julien N. P. Martel
Alexander W. Bergman
David B. Lindell
Gordon Wetzstein
AI4TS
128
2,548
0
17 Jun 2020
Implicit Regularization of Random Feature Models
Implicit Regularization of Random Feature Models
Arthur Jacot
Berfin Simsek
Francesco Spadaro
Clément Hongler
Franck Gabriel
59
83
0
19 Feb 2020
DeepXDE: A deep learning library for solving differential equations
DeepXDE: A deep learning library for solving differential equations
Lu Lu
Xuhui Meng
Zhiping Mao
George Karniadakis
PINN
AI4CE
97
1,528
0
10 Jul 2019
A Comparative Analysis of the Optimization and Generalization Property
  of Two-layer Neural Network and Random Feature Models Under Gradient Descent
  Dynamics
A Comparative Analysis of the Optimization and Generalization Property of Two-layer Neural Network and Random Feature Models Under Gradient Descent Dynamics
E. Weinan
Chao Ma
Lei Wu
MLT
55
123
0
08 Apr 2019
Learning Dynamical Systems from Partial Observations
Learning Dynamical Systems from Partial Observations
Ibrahim Ayed
Emmanuel de Bézenac
Arthur Pajot
J. Brajard
Patrick Gallinari
AI4TS
57
91
0
26 Feb 2019
Data Driven Governing Equations Approximation Using Deep Neural Networks
Data Driven Governing Equations Approximation Using Deep Neural Networks
Tong Qin
Kailiang Wu
D. Xiu
PINN
71
273
0
13 Nov 2018
Deep learning for universal linear embeddings of nonlinear dynamics
Deep learning for universal linear embeddings of nonlinear dynamics
Bethany Lusch
J. Nathan Kutz
Steven L. Brunton
71
1,250
0
27 Dec 2017
Direct likelihood-based inference for discretely observed stochastic
  compartmental models of infectious disease
Direct likelihood-based inference for discretely observed stochastic compartmental models of infectious disease
L. Ho
Forrest W. Crawford
M. Suchard
43
22
0
24 Aug 2016
Birth/birth-death processes and their computable transition
  probabilities with biological applications
Birth/birth-death processes and their computable transition probabilities with biological applications
L. Ho
Jason Xu
Forrest W. Crawford
V. Minin
M. Suchard
39
40
0
11 Mar 2016
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