Dilated Convolution for Time Series Learning
Wang Zhang, Subhro Das, et al.
ICASSP 2025
We report on random stimuli generation for hardware verification at IBM as a major application of various artificial intelligence technologies, including knowledge representation, expert systems, and constraint satisfaction. For more than a decade we have developed several related tools, with huge payoffs. Research and development around this application are still thriving, as we continue to cope with the ever-increasing complexity of modern hardware systems and demanding business environments. Copyright © 2007, American Association for Artificial Intelligence. All rights reserved.
Wang Zhang, Subhro Das, et al.
ICASSP 2025
Xiaoxiao Guo, Shiyu Chang, et al.
AAAI 2019
Albert Atserias, Anuj Dawar, et al.
Journal of the ACM
Guojing Cong, David A. Bader
Journal of Parallel and Distributed Computing