Empirical investigation requires dealing with fundamental uncertainty. In experimental psychology, research questions are often addressed using Null Hypothesis Significance Testing (NHST), an approach ...
Abstract: The exponential complexity growth of the very large-scale integration (VLSI) design space demands efficient automated parameter tuning of constraints. Confronting the dual limitations of ...
The full probability formula and Bayes' formula are important formulas in probability theory, mainly used to calculate the probability of more complex events, and they are essentially a combination of ...
PyVBMC is a Python implementation of the Variational Bayesian Monte Carlo (VBMC) algorithm for posterior and model inference, previously implemented in MATLAB. VBMC is an approximate inference method ...
Abstract: Real-world software–hardware co-design for AI accelerators must meet strict constraints on accuracy and PPA, making design space exploration both costly and inefficient. In this work, we ...
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