Fatnassi, Wael, Khedr, Haitham, Yamamoto, Valen, and Shoukry, Yasser. BERN-NN: Tight Bound Propagation For Neural Networks Using Bernstein Polynomial Interval Arithmetic. Retrieved from https://par.nsf.gov/biblio/10507110. Proceedings of the 26th ACM International Conference on Hybrid Systems: Computation and Control (HSCC 2023) . Web. doi:10.1145/3575870.3587126.

Fatnassi, Wael, Khedr, Haitham, Yamamoto, Valen, & Shoukry, Yasser. BERN-NN: Tight Bound Propagation For Neural Networks Using Bernstein Polynomial Interval Arithmetic. Proceedings of the 26th ACM International Conference on Hybrid Systems: Computation and Control (HSCC 2023), (). Retrieved from https://par.nsf.gov/biblio/10507110. https://doi.org/10.1145/3575870.3587126

Fatnassi, Wael, Khedr, Haitham, Yamamoto, Valen, and Shoukry, Yasser. "BERN-NN: Tight Bound Propagation For Neural Networks Using Bernstein Polynomial Interval Arithmetic". Proceedings of the 26th ACM International Conference on Hybrid Systems: Computation and Control (HSCC 2023) (). Country unknown/Code not available: ACM. https://doi.org/10.1145/3575870.3587126. https://par.nsf.gov/biblio/10507110.

@article{osti_10507110,
place = {Country unknown/Code not available}, title = {BERN-NN: Tight Bound Propagation For Neural Networks Using Bernstein Polynomial Interval Arithmetic}, url = {https://par.nsf.gov/biblio/10507110}, DOI = {10.1145/3575870.3587126}, abstractNote = {}, journal = {Proceedings of the 26th ACM International Conference on Hybrid Systems: Computation and Control (HSCC 2023)}, publisher = {ACM}, author = {Fatnassi, Wael and Khedr, Haitham and Yamamoto, Valen and Shoukry, Yasser}, }