Sure! Here's the revised description without any links: --- Want more on Polynomials? Take my Polynomial course for 50% off. Inside this course you will gain access to over 130 problems worked out ...

a notebook-first introduction to QSVT and QSP a reusable Python package for polynomial design, spectral transforms, and small PennyLane QSVT checks where the backend can synthesize the transform ...

The Simulated Bifurcation (SB) algorithm is a fast and highly parallelizable state-of-the-art algorithm for quadratic combinatorial optimization inspired by quantum physics and spins dynamics. It ...

Modeling marketing and pricing decisions based on historical data is one of the most efficient ways to guide business strategies. This article shows how statistics and programming work together to ...

Note: This content was generated by a crew of AI Agents developed by me. I have edited the code, though, because it was not good. In the bustling world of retail, e-commerce, and services, setting the ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Hydrocarbons are ubiquitous as fuels, solvents, lubricants, and as the principal ...

Specialized function gradient computing hardware could greatly improve the performance of state-of-the-art optimization algorithms. Prior work on such hardware, performed in the context of Ising ...

Abstract: Traveling salesman problem (TSP) is a problem of determining the shortest path for a salesman to take to visit all cities. Although a small number of cities is easy to solve, as the number ...

remove-circle Internet Archive's in-browser bookreader "theater" requires JavaScript to be enabled. It appears your browser does not have it turned on. Please see ...

In this paper, we present a novel means of control design for probabilistic movement primitives (ProMPs). Our proposed approach makes use of control barrier functions and control Lyapunov functions ...

Physics-Informed Neural Networks (PINN) are neural networks encoding the problem governing equations, such as Partial Differential Equations (PDE), as a part of the neural network. PINNs have emerged ...