A brand new technical paper titled “Bayesian dropout approximation in deep studying neural networks: evaluation of self-aligned quadruple patterning” was revealed by researchers at IBM TJ Watson Analysis Heart and Rensselaer Polytechnic Institute.

Discover the technical paper here. Printed November 2022.  Open Entry.

Scott D. Halle, Derren N. Dunn, Allen H. Gabor, Max O. Bloomfield, and Mark Shephard “Bayesian dropout approximation in deep studying neural networks: evaluation of self-aligned quadruple patterning,” Journal of Micro/Nanopatterning, Supplies, and Metrology 21(4), 041604 (eight November 2022). https://doi.org/10.1117/1.JMM.21.4.041604.

The submit Using BDA To to Predict SAQP Pitch Walk appeared first on Semiconductor Engineering.



Source link

LEAVE A REPLY

Please enter your comment!
Please enter your name here