![Estimation Of Post-Nonlinear Causal Models Using Autoencoding Structure](/assets/initial/large/0.jpg)
Already purchased this program?
Login to View
This video program is a part of the Premium package:
Estimation Of Post-Nonlinear Causal Models Using Autoencoding Structure
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Estimation Of Post-Nonlinear Causal Models Using Autoencoding Structure
Discovering causal relations in complex systems is an important problem in many research fields. To describe such systems involving nonlinear causal relations, the post-nonlinear (PNL) causal model has been proposed. However, despite its identifiability,
Discovering causal relations in complex systems is an important problem in many research fields. To describe such systems involving nonlinear causal relations, the post-nonlinear (PNL) causal model has been proposed. However, despite its identifiability,