In this video, we implement the Adam optimization algorithm from scratch using pure Python. You'll learn how Adam combines the benefits of momentum and RMSProp, and how it updates weights ...

In this paper we study optimization problems with variational inequality constraints in finite dimensional spaces. Kuhn-Tucker type necessary optimality conditions involving coderivatives are given ...

We propose a novel, scalable deep Bayesian optimization (BO) methodology for designing antennas with a large number of design degrees of freedom. Conventional BO approaches in antenna design have ...

This paper presents a user-adaptive variable impedance control approach for robot-aided rehabilitation, initially focusing on an ankle rehabilitation application. The controller dynamically adjusts ...

Bayesian statistical methods offer a flexible and powerful framework for approaching a variety of data science problems. They provide results that are interpretable and naturally incorporate relevant ...

Bayesian Methods for Hackers Using Python and PyMC The Bayesian method is the natural approach to inference, yet it is hidden from readers behind chapters of slow, mathematical analysis. The typical ...

SEEQC folds clocking, pulse generation, feedback, and routing into a chip-level platform that sits inside the cryostat.