Search Results - extrapolation adversarial variational autoencoder*

Study on data augmentation with physics-informed generative adversarial networks and the extrapolation performance of COP prediction for chillers by Wang, Zhengyang, Chen, Jun, Guo, Kexin, Xu, Bo, Chen, Zhenqian

“…•Vendi Score and Mahalanobis distance quantify data diversity and extrapolation risk.•Physics-informed samples enhance physical consistency and statistical reliability…”
Get full text

Deep Generative Modeling of Periodic Variable Stars Using Physical Parameters by Martínez-Palomera, Jorge, Bloom, Joshua S., Abrahams, Ellianna S.

“… Unlike fully theory-driven models, these approaches do not typically allow principled interpolation nor extrapolation…”
Get full text

Improving the Performance of Batch-Constrained Reinforcement Learning in Continuous Action Domains via Generative Adversarial Networks by Saglam, Baturay, Dalmaz, Onat, Gonc, Kaan, Kozat, Suleyman S.

“… However, due to conditional Variational Autoencoders (VAE) used in the data generation module, the BCQ algorithm optimizes a lower variational bound and hence, it is not generalizable to environments with large state and action spaces…”
Get full text

One-shot generative distribution matching for augmented RF-based UAV identification by Kazemi, Amir, Basiri, Salar, Kindratenko, Volodymyr, Salapaka, Srinivasa

“…) and variational autoencoders (VAEs). The paper provides a theoretical guarantee for the effectiveness…”
Get full text

NEURAL ORDINARY DIFFERENTIAL EQUATIONS FOR TIME SERIES RECONSTRUCTION by Androsov, D. V.

“… of unevenly distributed samples. Objective. The goal of the following research is the synthesis of a deep neural network that is able to solve input signal reconstruction and time series extrapolation task. Method…”
Get full text

Study of Deep Generative Models for Inorganic Chemical Compositions by Sawada, Yoshihide, Morikawa, Koji, Fujii, Mikiya

“…Generative models based on generative adversarial networks (GANs) and variational autoencoders (VAEs…”
Get full text

Deep Generative Modeling of Periodic Variable Stars Using Physical Parameters by Martínez-Palomera, Jorge, Bloom, Joshua S, Abrahams, Ellianna S

“… Unlike fully theory-driven models, these approaches do not typically allow principled interpolation nor extrapolation…”
Get full text