To enable more accurate estimation of connectivity, we propose a data-driven and theoretically grounded framework for optimally designing perturbation inputs, based on formulating the neural model as ...

Abstract: This article proposes a data-driven model-free inverse Q-learning algorithm for continuous-time linear quadratic regulators (LQRs). Using an agent’s trajectories of states and optimal ...

In their warped and wrongheaded way, the omnipresent influencer Clavicular and his looksmaxxing compatriots are intent on demystifying the ideal of natural beauty.

This research advances hybrid soft-rigid robot simulations, achieving up to 1000 times faster computations through analytical derivatives in the GVS framework.

In Mathematics, there are no shortcuts to understanding, but there are definitely smarter paths to scoring well.

Abstract: Seismic inversion and petrophysical inversion are the most common methods used in exploration geophysics to obtain elastic and petrophysical parameters, which are essential for reservoir ...