American Psychological Association 6th edition

Bolte, J., & Pauwels, E. (2020). Conservative set valued fields, automatic differentiation, stochastic gradient methods and deep learning. Mathematical Programming: A Publication of the Mathematical Optimization Society, 1-33. https://doi.org/10.1007/s10107-020-01501-5

ISO-690 (author-date, English)

BOLTE, Jérôme and PAUWELS, Edouard, 2020. Conservative set valued fields, automatic differentiation, stochastic gradient methods and deep learning. Mathematical Programming: A Publication of the Mathematical Optimization Society. 15 April 2020. P. 1-33. DOI 10.1007/s10107-020-01501-5.

Modern Language Association 9th edition

Bolte, J., and E. Pauwels. “Conservative Set Valued Fields, Automatic Differentiation, Stochastic Gradient Methods and Deep Learning”. Mathematical Programming: A Publication of the Mathematical Optimization Society, Apr. 2020, pp. 1-33, https://doi.org/10.1007/s10107-020-01501-5.

Mohr Siebeck - Recht (Deutsch - Österreich)

Bolte, Jérôme/Pauwels, Edouard: Conservative set valued fields, automatic differentiation, stochastic gradient methods and deep learning, Mathematical Programming: A Publication of the Mathematical Optimization Society 2020, 1-33.

Emerald - Harvard

Bolte, J. and Pauwels, E. (2020), “Conservative set valued fields, automatic differentiation, stochastic gradient methods and deep learning”, Mathematical Programming: A Publication of the Mathematical Optimization Society, pp. 1-33.

Warning: These citations may not always be 100% accurate.