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Non-linear dimension reduction in factor-augmented vector
  autoregressions

Non-linear dimension reduction in factor-augmented vector autoregressions

9 September 2023
K. Klieber
ArXivPDFHTML

Papers citing "Non-linear dimension reduction in factor-augmented vector autoregressions"

9 / 9 papers shown
Title
Improving KernelSHAP: Practical Shapley Value Estimation via Linear
  Regression
Improving KernelSHAP: Practical Shapley Value Estimation via Linear Regression
Ian Covert
Su-In Lee
FAtt
54
170
0
02 Dec 2020
Nowcasting in a Pandemic using Non-Parametric Mixed Frequency VARs
Nowcasting in a Pandemic using Non-Parametric Mixed Frequency VARs
Florian Huber
Gary Koop
Luca Onorante
Michael Pfarrhofer
Josef Schreiner
31
84
0
28 Aug 2020
Deep Dynamic Factor Models
Deep Dynamic Factor Models
P. Andreini
Cosimo Izzo
G. Ricco
28
11
0
23 Jul 2020
Deep Factors for Forecasting
Deep Factors for Forecasting
Bernie Wang
Alex Smola
Danielle C. Maddix
Jan Gasthaus
Dean Phillips Foster
Tim Januschowski
BDL
54
173
0
28 May 2019
Deep Neural Networks for Estimation and Inference
Deep Neural Networks for Estimation and Inference
M. Farrell
Tengyuan Liang
S. Misra
BDL
143
254
0
26 Sep 2018
Deep Learning for Predicting Asset Returns
Deep Learning for Predicting Asset Returns
Guanhao Feng
Jingyu He
Nicholas G. Polson
43
58
0
25 Apr 2018
Ancillarity-Sufficiency Interweaving Strategy (ASIS) for Boosting MCMC
  Estimation of Stochastic Volatility Models
Ancillarity-Sufficiency Interweaving Strategy (ASIS) for Boosting MCMC Estimation of Stochastic Volatility Models
G. Kastner
Sylvia Fruhwirth-Schnatter
35
296
0
16 Jun 2017
Bayesian Approximate Kernel Regression with Variable Selection
Bayesian Approximate Kernel Regression with Variable Selection
Lorin Crawford
K. Wood
Xiaoping Zhou
Sayan Mukherjee
53
44
0
05 Aug 2015
Representation Learning: A Review and New Perspectives
Representation Learning: A Review and New Perspectives
Yoshua Bengio
Aaron Courville
Pascal Vincent
OOD
SSL
222
12,422
0
24 Jun 2012
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