Results 111 to 120 of about 391,078 (263)
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley +1 more source
Quadrotor unmanned aerial vehicle control is critical to maintain flight safety and efficiency, especially when facing external disturbances and model uncertainties. This article presents a robust reinforcement learning control scheme to deal with these challenges.
Yu Cai +3 more
wiley +1 more source
A biologically plausible decision-making model based on interacting neural populations. [PDF]
Baspinar E +8 more
europepmc +1 more source
Variational Autoencoder+Deep Deterministic Policy Gradient addresses low‐light failures of infrared depth sensing for indoor robot navigation. Stage 1 pretrains an attention‐enhanced Variational Autoencoder (Convolutional Block Attention Module+Feature Pyramid Network) to map dark depth frames to a well‐lit reconstruction, yielding a 128‐D latent code ...
Uiseok Lee +7 more
wiley +1 more source
Computational frameworks for automated detection and quantification of paroxysmal sympathetic hyperactivity among traumatic brain injury patients. [PDF]
Kong X +7 more
europepmc +1 more source
Context Awareness and Human–Robot Interaction Optimization for Museum Intelligent Guide Robot
This study presents a context‐aware human–robot interaction framework designed for intelligent museum guide robots. The system features a three‐layer architecture—perception, understanding, and behavior execution—that enables adaptive and meaningful interactions with museum visitors.
Anna Zou, Yue Meng, Shijing Tong
wiley +1 more source
Trade Realignments and the Need for Integrated Modeling Research in Latin America's Agri‐Food Sector
Agribusiness, EarlyView.
Emiliano Lopez Barrera
wiley +1 more source
The pursuit‐evasion game is studied for two adversarial active agents, modeled as deterministic self‐steering pursuer and stochastic, cognitive evader. For a successful evasion strategy, the motile target has to exploit all available pursuer information, e.g., by tuning the tumbling frequency with the pursuer distance.
Segun Goh +2 more
wiley +1 more source
Enabling Episode-Level Transparency in Value-Based Care Through Large Language Model-Driven Provider Directories. [PDF]
Kodan A.
europepmc +1 more source

