Kai Zhou

According to our database, Kai Zhou authored at least 23 papers between 2016 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of five.

2025

Combining complex Langevin dynamics with score-based and energy-based diffusion models.

Gert Aarts, Diaa E. Habibi, Lingxiao Wang, Kai Zhou

CoRR, October, 2025

Unifying Physics- and Data-Driven Modeling via Novel Causal Spatiotemporal Graph Neural Network for Interpretable Epidemic Forecasting.

Shuai Han, Lukas Stelz, Thomas R. Sokolowski, Kai Zhou, Horst Stöcker

CoRR, April, 2025

On learning higher-order cumulants in diffusion models.

Gert Aarts, Diaa E. Habibi, Lingxiao Wang, Kai Zhou

Mach. Learn. Sci. Technol., 2025

Epidemiology-informed Spatiotemporal Graph Neural Network for heterogeneity-driven interpretable epidemic forecasting.

Shuai Han, Lukas Stelz, Thomas R. Sokolowski, Kai Zhou, Horst Stöcker

Eng. Appl. Artif. Intell., 2025

Hybrid multi-head physics-informed neural network for depth estimation in terahertz imaging.

Mingjun Xiang, Hui Yuan, Kai Zhou, Hartmut G. Roskos

Comput. Phys. Commun., 2025

2024

DiaaEddinH/On-learning-higher-order-cumulants-in-diffusion-models: v1.0.2.

Diaa E. Habibi, Gert Aarts, Lingxiao Wang, Kai Zhou

Dataset, October, 2024

DiaaEddinH/On-learning-higher-order-cumulants-in-diffusion-models: v1.0.1.

Diaa Eddin Habibi, Gert Aarts, Lingxiao Wang, Kai Zhou

Dataset, October, 2024

Approaching epidemiological dynamics of COVID-19 with physics-informed neural networks.

Shuai Han, Lukas Stelz, Horst Stoecker, Lingxiao Wang, Kai Zhou

J. Frankl. Inst., 2024

Hierarchical cavitation intensity recognition using Sub-Master Transition Network-based acoustic signals in pipeline systems.

Shuiping Gou, Yu Sha, Bo Liu, Ningtao Liu, Johannes Faber, Stefan Schramm, Horst Stoecker, Thomas Steckenreiter, Domagoj Vnucec, Nadine Wetzstein, Andreas Widl, Kai Zhou

Expert Syst. Appl., 2024

Diffusion models learn distributions generated by complex Langevin dynamics.

Diaa E. Habibi, Gert Aarts, Lingxiao Wang, Kai Zhou

CoRR, 2024

Hierarchical Knowledge Guided Fault Intensity Diagnosis of Complex Industrial Systems.

Yu Sha, Shuiping Gou, Bo Liu, Johannes Faber, Ningtao Liu, Stefan Schramm, Horst Stoecker, Thomas Steckenreiter, Domagoj Vnucec, Nadine Wetzstein, Andreas Widl, Kai Zhou

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

2023

Rethinking the ill-posedness of the spectral function reconstruction - Why is it fundamentally hard and how Artificial Neural Networks can help.

Shuzhe Shi, Lingxiao Wang, Kai Zhou

Comput. Phys. Commun., 2023

Optimal Power Flow in Highly Renewable Power System Based on Attention Neural Networks.

Chen Li, Alexander Kies, Kai Zhou, Markus Schlott, Omar El Sayed, Mariia Bilousova, Horst Stoecker

CoRR, 2023

Generative Diffusion Models for Lattice Field Theory.

Lingxiao Wang, Gert Aarts, Kai Zhou

CoRR, 2023

Diffusion Models as Stochastic Quantization in Lattice Field Theory.

Lingxiao Wang, Gert Aarts, Kai Zhou

CoRR, 2023

2022

Shared Data and Algorithms for Deep Learning in Fundamental Physics.

Lisa Benato, Erik Buhmann, Martin Erdmann, Peter Fackeldey, Jonas Glombitza, Nikolai Hartmann, Gregor Kasieczka, William Korcari, Thomas Kuhr, Jan Steinheimer, Horst Stöcker, Tilman Plehn, Kai Zhou

Comput. Softw. Big Sci., December, 2022

A multi-task learning for cavitation detection and cavitation intensity recognition of valve acoustic signals.

Yu Sha, Johannes Faber, Shuiping Gou, Bo Liu, Wei Li, Stefan Schramm, Horst Stoecker, Thomas Steckenreiter, Domagoj Vnucec, Nadine Wetzstein, Andreas Widl, Kai Zhou

Eng. Appl. Artif. Intell., 2022

An acoustic signal cavitation detection framework based on XGBoost with adaptive selection feature engineering.

Yu Sha, Johannes Faber, Shuiping Gou, Bo Liu, Wei Li, Stefan Schramm, Horst Stöcker, Thomas Steckenreiter, Domagoj Vnucec, Nadine Wetzstein, Andreas Widl, Kai Zhou

CoRR, 2022

Regional-Local Adversarially Learned One-Class Classifier Anomalous Sound Detection in Global Long-Term Space.

Yu Sha, Shuiping Gou, Johannes Faber, Bo Liu, Wei Li, Stefan Schramm, Horst Stoecker, Thomas Steckenreiter, Domagoj Vnucec, Nadine Wetzstein, Andreas Widl, Kai Zhou

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

2021

Machine learning spatio-temporal epidemiological model to evaluate Germany-county-level COVID-19 risk.

Lingxiao Wang, Tian Xu, Till Hannes Stoecker, Horst Stöcker, Yin Jiang, Kai Zhou

Mach. Learn. Sci. Technol., 2021

Automatic differentiation approach for reconstructing spectral functions with neural networks.

Lingxiao Wang, Shuzhe Shi, Kai Zhou

CoRR, 2021

Reconstructing spectral functions via automatic differentiation.

Lingxiao Wang, Shuzhe Shi, Kai Zhou

CoRR, 2021

2016

An EoS-meter of QCD transition from deep learning.

Long-Gang Pang, Kai Zhou, Nan Su, Hannah Petersen, Horst Stöcker, Xin-Nian Wang

CoRR, 2016