Why quasi-Monte Carlo is better than Monte Carlo or Latin hypercube sampling for statistical circuit analysis
A Singhee, RA Rutenbar - IEEE Transactions on Computer …, 2010 - ieeexplore.ieee.org
At the nanoscale, no circuit parameters are truly deterministic; most quantities of practical
interest present themselves as probability distributions. Thus, Monte Carlo techniques …
interest present themselves as probability distributions. Thus, Monte Carlo techniques …
Why quasi-Monte Carlo is better than Monte Carlo or Latin hypercube sampling for statistical circuit analysis
A Singhee, RA Rutenbar - IEEE TCADIS, 2010 - research.ibm.com
At the nanoscale, no circuit parameters are truly deterministic; most quantities of practical
interest present themselves as probability distributions. Thus, Monte Carlo techniques …
interest present themselves as probability distributions. Thus, Monte Carlo techniques …
Why quasi-Monte Carlo is better than Monte Carlo or Latin hypercube sampling for statistical circuit analysis
A Singhee, RA Rutenbar - IEEE Transactions on Computer …, 2010 - experts.illinois.edu
At the nanoscale, no circuit parameters are truly deterministic; most quantities of practical
interest present themselves as probability distributions. Thus, Monte Carlo techniques …
interest present themselves as probability distributions. Thus, Monte Carlo techniques …
Why quasi-Monte Carlo is better than monte carlo or latin hypercube sampling for statistical circuit analysis
A Singhee, RA Rutenbar - … Transactions on Computer-Aided Design of …, 2010 - dl.acm.org
At the nanoscale, no circuit parameters are truly deterministic; most quantities of practical
interest present themselves as probability distributions. Thus, Monte Carlo techniques …
interest present themselves as probability distributions. Thus, Monte Carlo techniques …
Why Quasi-Monte Carlo is Better Than Monte Carlo or Latin Hypercube Sampling for Statistical Circuit Analysis
A Singhee, RA Rutenbar - IEEE Transactions on Computer-Aided Design …, 2010 - infona.pl
At the nanoscale, no circuit parameters are truly deterministic; most quantities of practical
interest present themselves as probability distributions. Thus, Monte Carlo techniques …
interest present themselves as probability distributions. Thus, Monte Carlo techniques …
Why Quasi-Monte Carlo is Better Than Monte Carlo or Latin Hypercube Sampling for Statistical Circuit Analysis
A Singhee, RA Rutenbar - IEEE Transactions on Computer-Aided Design …, 2010 - infona.pl
At the nanoscale, no circuit parameters are truly deterministic; most quantities of practical
interest present themselves as probability distributions. Thus, Monte Carlo techniques …
interest present themselves as probability distributions. Thus, Monte Carlo techniques …