An EoS-meter of QCD transition from deep learning. - Long-Gang Pang; Kai Zhou 017; Nan Su; Hannah Petersen; Horst Stöcker; Xin-Nian Wang (CoRR, 2016)

Reconstructing spectral functions via automatic differentiation. - Lingxiao Wang 006; Shuzhe Shi; Kai Zhou 017 (CoRR, 2021)

Automatic differentiation approach for reconstructing spectral functions with neural networks. - Lingxiao Wang 006; Shuzhe Shi; Kai Zhou 017 (CoRR, 2021)

Machine learning spatio-temporal epidemiological model to evaluate Germany-county-level COVID-19 risk. - Lingxiao Wang 006; Tian Xu; Till Hannes Stoecker; Horst Stöcker; Yin Jiang; Kai Zhou 017 (Mach. Learn. Sci. Technol., 2021)

Regional-Local Adversarially Learned One-Class Classifier Anomalous Sound Detection in Global Long-Term Space. - Yu Sha; Shuiping Gou; Johannes Faber; Bo Liu 009; Wei Li; Stefan Schramm; Horst Stoecker; Thomas Steckenreiter; Domagoj Vnucec; Nadine Wetzstein; Andreas Widl; Kai Zhou 017 (KDD, 2022)

An acoustic signal cavitation detection framework based on XGBoost with adaptive selection feature engineering. - Yu Sha; Johannes Faber; Shuiping Gou; Bo Liu 009; Wei Li; Stefan Schramm; Horst Stöcker; Thomas Steckenreiter; Domagoj Vnucec; Nadine Wetzstein; Andreas Widl; Kai Zhou 017 (CoRR, 2022)

A multi-task learning for cavitation detection and cavitation intensity recognition of valve acoustic signals. - Yu Sha; Johannes Faber; Shuiping Gou; Bo Liu 009; Wei Li; Stefan Schramm; Horst Stoecker; Thomas Steckenreiter; Domagoj Vnucec; Nadine Wetzstein; Andreas Widl; Kai Zhou 017 (Eng. Appl. Artif. Intell., 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; et al. (Comput. Softw. Big Sci., 2022)

Diffusion Models as Stochastic Quantization in Lattice Field Theory. - Lingxiao Wang 006; Gert Aarts; Kai Zhou 017 (CoRR, 2023)

Generative Diffusion Models for Lattice Field Theory. - Lingxiao Wang 006; Gert Aarts; Kai Zhou 017 (CoRR, 2023)

Optimal Power Flow in Highly Renewable Power System Based on Attention Neural Networks. - Chen Li; Alexander Kies; Kai Zhou 017; Markus Schlott; Omar El Sayed; Mariia Bilousova; Horst Stoecker (CoRR, 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 006; Kai Zhou 017 (Comput. Phys. Commun., 2023)

Hierarchical Knowledge Guided Fault Intensity Diagnosis of Complex Industrial Systems. - Yu Sha; Shuiping Gou; Bo Liu 009; Johannes Faber; Ningtao Liu; Stefan Schramm; Horst Stoecker; Thomas Steckenreiter; Domagoj Vnucec; Nadine Wetzstein; Andreas Widl; Kai Zhou 017 (KDD, 2024)

Diffusion models learn distributions generated by complex Langevin dynamics. - Diaa E. Habibi; Gert Aarts; Lingxiao Wang 006; Kai Zhou 017 (CoRR, 2024)

Hierarchical cavitation intensity recognition using Sub-Master Transition Network-based acoustic signals in pipeline systems. - Shuiping Gou; Yu Sha; Bo Liu 009; Ningtao Liu; Johannes Faber; Stefan Schramm; Horst Stoecker; Thomas Steckenreiter; Domagoj Vnucec; Nadine Wetzstein; Andreas Widl; Kai Zhou 017 (Expert Syst. Appl., 2024)

Approaching epidemiological dynamics of COVID-19 with physics-informed neural networks. - Shuai Han; Lukas Stelz; Horst Stoecker; Lingxiao Wang 006; Kai Zhou 017 (J. Frankl. Inst., 2024)

DiaaEddinH/On-learning-higher-order-cumulants-in-diffusion-models: v1.0.1. - Diaa Eddin Habibi; Gert Aarts; Lingxiao Wang 006; Kai Zhou 017 (Zenodo, 2024)

DiaaEddinH/On-learning-higher-order-cumulants-in-diffusion-models: v1.0.2. - Diaa E. Habibi; Gert Aarts; Lingxiao Wang 006; Kai Zhou 017 (Zenodo, 2024)

Hybrid multi-head physics-informed neural network for depth estimation in terahertz imaging. - Mingjun Xiang; Hui Yuan; Kai Zhou 017; Hartmut G. Roskos (Comput. Phys. Commun., 2025)

Epidemiology-informed Spatiotemporal Graph Neural Network for heterogeneity-driven interpretable epidemic forecasting. - Shuai Han; Lukas Stelz; Thomas R. Sokolowski; Kai Zhou 017; Horst Stöcker (Eng. Appl. Artif. Intell., 2025)

On learning higher-order cumulants in diffusion models. - Gert Aarts; Diaa E. Habibi; Lingxiao Wang 006; Kai Zhou 017 (Mach. Learn. Sci. Technol., 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 017; Horst Stöcker (CoRR, 2025)

Combining complex Langevin dynamics with score-based and energy-based diffusion models. - Gert Aarts; Diaa E. Habibi; Lingxiao Wang 006; Kai Zhou 017 (CoRR, 2025)