Results 71 to 80 of about 251,998 (281)

Factorizing Probabilistic Graphical Models Using Co-occurrence Rate [PDF]

, 2011
Factorization is of fundamental importance in the area of Probabilistic Graphical Models (PGMs). In this paper, we theoretically develop a novel mathematical concept, \textbf{C}o-occurrence \textbf{R}ate (CR), for factorizing PGMs.
Zhu, Zhemin
core   +2 more sources

gnSPADE: Incorporating Gene Network Structures Enhances Reference‐Free Deconvolution in Spatial Transcriptomics

Advanced Intelligent Systems, EarlyView.
gnSPADE integrates gene‐network structures into a probabilistic topic modeling framework to achieve reference‐free cell‐type deconvolution in spatial transcriptomics. By embedding gene connectivity within the generative process, gnSPADE enhances biological interpretability and accuracy across simulated and real datasets, revealing spatial organization ...
Aoqi Xie, Yuehua Cui
wiley   +1 more source

Bayesian Markov Random Field analysis for protein function prediction based on network data. [PDF]

PLoS ONE, 2010
Inference of protein functions is one of the most important aims of modern biology. To fully exploit the large volumes of genomic data typically produced in modern-day genomic experiments, automated computational methods for protein function prediction ...
Yiannis A I Kourmpetis, Aalt D J van Dijk, Marco C A M Bink, Roeland C H J van Ham, Cajo J F ter Braak   +4 more
doaj   +1 more source

Combinatorial Markov Random Fields [PDF]

, 2006
A combinatorial random variable is a discrete random variable defined over a combinatorial set (e.g., a power set of a given set). In this paper we introduce combinatorial Markov random fields (Comrafs), which are Markov random fields where some of the nodes are combinatorial random variables.
Bekkerman, R, Sahami, M, Learned-Miller, E   +2 more
openaire   +1 more source

Feature Disentangling and Combination Implemented by Spin–Orbit Torque Magnetic Tunnel Junctions

Advanced Intelligent Systems, EarlyView.
Spin–orbit torque magnetic tunnel junctions (SOT‐MTJs) enable efficient feature disentangling and integration in image data. A proposed algorithm leverages SOT‐MTJs as true random number generators to disentangle and recombine features in real time, with experimental validation on emoji and facial datasets.
Xiaohan Li, Yingqian Xu, Caihua Wan, Ran Zhang, Meike Hindenberg, Raik Hoffmann, Shiqiang Liu, Tianyi Zhang, Shilong Xiong, Dehao Kong, Jihao Xia, Fangshuo Gao, Zhuyang Nie, Thomas Kämpfe, Guoqiang Yu, Xiufeng Han   +15 more
wiley   +1 more source

High‐order Markov random field for single depth image super‐resolution

IET Computer Vision, 2017
Although there is an increasing interest in employing the depth data in computer vision applications, the spatial resolution of depth maps is still limited compared with typical visible‐light images.
Elham Shabaninia, Ahmad Reza Naghsh‐Nilchi, Shohreh Kasaei   +2 more
doaj   +1 more source

A JOINT PIXEL AND REGION BASED MULTISCALE MARKOV RANDOM FIELD FOR IMAGE CLASSIFICATION [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2012
MRF model is recognized as one of efficient tools for image classification. However, traditional MRF model prove to be limited for high resolution image classification.
T. Mei, L. Zheng, S. Zhong
doaj   +1 more source

Adaptive Autonomy in Microrobot Motion Control via Deep Reinforcement Learning and Path Planning Synergy

Advanced Intelligent Systems, EarlyView.
This study introduces a data‐driven framework that combines deep reinforcement learning with classical path planning to achieve adaptive microrobot navigation. By training a surrogate neural network to emulate microrobot dynamics, the approach improves learning efficiency, reduces training time, and enables robust real‐time obstacle avoidance in ...
Amar Salehi, Bairong Zhu, Haoyu Liu, Tingting Yu   +3 more
wiley   +1 more source

Collaborative Multiagent Closed‐Loop Motion Planning for Multimanipulator Systems

Advanced Intelligent Systems, EarlyView.
This work presents a hierarchical multi‐manipulator planner, emphasizing highly overlapping space. The proposed method leverages an enhanced Dynamic Movement Primitive based planner along with an improvised Multi‐Agent Reinforcement Learning approach to ensure regulatory and mediatory control while ensuring low‐level autonomy. Experiments across varied
Tian Xu, Siddharth Singh, Qing Chang
wiley   +1 more source

Language‐Guided Robot Grasping Based on Basic Geometric Shape Fitting

Advanced Intelligent Systems, EarlyView.
This article presents a language‐guided, model‐free grasping framework that integrates multimodal perception with primitive‐based geometric fitting. By explicitly modeling object geometry from RGB‐D data, the method enables semantically controllable grasp pose generation and achieves robust performance in both structured and cluttered real‐world ...
Qun Niu, Chuanlin Zhang, Tianyu Zhang, Jieliang Zhao, Tie Fu, Xuemei Chen   +5 more
wiley   +1 more source