WiMi Releases Next-Generation Quantum Convolutional Neural Network Technology for Multi-Channel Supervised Learning BEIJING, Jan. 05, 2026––WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the ...

The goal of this assignment was to develop a program in C that is capable of solving first-order linear systems of equations. These systems are of the form Ax=b, where A is a known matrix, b is a ...

Automated three-stage analysis pipeline sifts out whale calls from terabytes of distributed acoustic sensing data.

In recent years, several serious traffic accidents have exposed the shortcomings of current autonomous driving systems in making safe decisions ...

Abstract: Recent developments in cyber-physical systems have increased the importance of maximizing the freshness of the information about the physical environment. However, optimizing the access ...

Abstract: Policy Gradient is a policy-based reinforcement learning algorithm that approximates the optimal policy through a parametric function. The algorithm classifies the observations by softmax ...

In this study, we focus on investigating a nonsmooth convex optimization problem involving the l 1-norm under a non-negative constraint, with the goal of developing an inverse-problem solver for image ...

The study, titled Reinforcement Learning for Monetary Policy Under Macroeconomic Uncertainty: Analyzing Tabular and Function ...

Department of Radiology, Jinling Hospital, Affiliated Nanjing Medical University, Nanjing 210002, China Department of Radiology, The Affiliated Jiangning Hospital of Nanjing Medical University, ...

Policy gradient methods have significantly advanced the reasoning capabilities of LLMs, particularly through RL. A key tool in stabilizing these methods is Kullback-Leibler (KL) regularization, which ...