Since its development 100 years ago, quantum mechanics has revolutionized our understanding of nature, revealing a bizarre ...

Everything is now opaque. Here's why marketers must shift from chasing visibility to shaping the signals models remember and ...

We propose a Causal Diffused Graph- Transformer Network (CDGTN) to extract features from the source-reply graph in a social media conversation. Then, we propose source-guided incremental attention ...

We do also develop an axiomatically determined theory for implementing a discrete analogue of the proposed time-causal frequency analysis method on discrete data, based on first-order recursive ...

The effective graph we introduce synthesizes both the causal interaction structure and the nonlinear dynamics of BNs into a single scalable graph formalism. We use 78 experimentally validated BN ...

A causal model graph represents a network of interconnected entities and relationships, enabling the system to understand how various factors influence each other to create an optimized outcome.

In this paper, the near optimal control problem of discrete-time switched nonlinear system with hysteresis is studied, that is, an optimal control scheme is designed for the approximate model of ...