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[n]	A. Scheinker, “Generative deep learning for 6D phase space diagnostics via physics-constrained neural networks, physics models, and adaptive feedback”, in Proc. IPAC'24, Nashville, TN, USA, May 2024, pp. 1827-1830. doi:10.18429/JACoW-IPAC2024-TUPS66

[n]	P. Sha et al., “Pre-study of CEPC SRF Cavity”, in Proc. LINAC'18, Beijing, China, Sep. 2018, pp. 476-479. doi:10.18429/JACoW-LINAC2018-TUPO064

For LaTeX

%\cite{Scheinker:IPAC24-TUPS66} \bibitem{Scheinker:IPAC24-TUPS66} A. Scheinker, \textquotedblleft{Generative deep learning for 6D phase space diagnostics via physics-constrained neural networks, physics models, and adaptive feedback}\textquotedblright, in \emph{Proc. IPAC’24}, Nashville, TN, USA, May 2024, pp. 1827--1830. \doi{10.18429/JACoW-IPAC2024-TUPS66} %\cite{Sha:LINAC18-TUPO064} \bibitem{Sha:LINAC18-TUPO064} P. Sha \emph{et al.}, \textquotedblleft{Pre-study of CEPC SRF Cavity}\textquotedblright, in \emph{Proc. LINAC’18}, Beijing, China, Sep. 2018, pp. 476--479. \doi{10.18429/JACoW-LINAC2018-TUPO064}

For BibTeX

@inproceedings{scheinker:ipac24-tups66, author = {A. Scheinker}, title = {{Generative deep learning for 6D phase space diagnostics via physics-constrained neural networks, physics models, and adaptive feedback}}, booktitle = {Proc. IPAC'24}, pages = {1827--1830}, paper = {TUPS66}, venue = {Nashville, TN, USA}, series = {International Particle Accelerator Conference}, number = {15}, publisher = {JACoW Publishing, Geneva, Switzerland}, month = {7}, year = {2024}, issn = {2673-5490}, isbn = {978-3-95-450247-9}, doi = {10.18429/JACoW-IPAC2024-TUPS66}, language = {english} } @inproceedings{sha:linac18-tupo064, author = {P. Sha and others}, title = {{Pre-study of CEPC SRF Cavity}}, booktitle = {Proc. LINAC'18}, pages = {476--479}, paper = {TUPO064}, venue = {Beijing, China}, series = {Linear Accelerator Conference}, number = {29}, publisher = {JACoW Publishing, Geneva, Switzerland}, month = {1}, year = {2019}, issn = {2226-0366}, isbn = {978-3-95-450194-6}, doi = {10.18429/JACoW-LINAC2018-TUPO064}, url = {https://jacow.org/linac2018/papers/TUPO064.pdf}, language = {english} }

References

• A. Scheinker, “Generative deep learning for 6D phase space diagnostics via physics-constrained neural networks, physics models, and adaptive feedback”, in Proc. 15th Int. Particle Accelerator Conf. (IPAC'24), Nashville, TN, USA, May 2024, paper TUPS66, pp. 1827-1830.
• P. Sha et al., “Pre-study of CEPC SRF Cavity”, in Proc. 29th Linear Accelerator Conf. (LINAC'18), Beijing, China, Sep. 2018, pp. 476-479.