Results 101 to 110 of about 3,865,632 (281)

Bayesian network structure learning by dynamic programming algorithm based on node block sequence constraints

CAAI Transactions on Intelligence Technology
The use of dynamic programming (DP) algorithms to learn Bayesian network structures is limited by their high space complexity and difficulty in learning the structure of large‐scale networks.
Chuchao He, Ruohai Di, Bo Li, Evgeny Neretin   +3 more
doaj   +1 more source

Transcendental model selection: a computational account of symbolic cognition and general intelligence through morality and culture

Frontiers in Sociology
General intelligence enables flexible problem solving across diverse contexts by minimizing uncertainty. Symbolic systems such as language extend this capacity, allowing humans to build social groups and construct world models beyond typical biological ...
Shagor Rahman, Andrew Pashea
doaj   +1 more source

Comparing the Effect of Semi‐Immersive Virtual Reality, Computerized Cognitive Training, and Traditional Rehabilitation on Cognitive Function in Multiple Sclerosis: A Randomized Clinical Trial

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Cognitive impairment is a common non‐motor symptom in Multiple Sclerosis (MS), negatively affecting autonomy and Quality of Life (QoL). Innovative rehabilitation strategies, such as semi‐immersive virtual reality (VR) and computerized cognitive training (CCT), may offer advantages over traditional cognitive rehabilitation (TCR ...
Maria Grazia Maggio, Desiree Latella, Lilla Bonanno, Paulo Cezar Rocha dos Santos, Marcos Maldonado‐Díaz, Meir Plotnik, Rosaria De Luca, Angelo Quartarone, Rocco Salvatore Calabrò   +8 more
wiley   +1 more source

Learning Structures Through Reinforcement

, 2018
How the brain uses reinforcement feedback to make simple choices that lead to reward is well understood. However, this ability is often considered insufficient to account for the flexibility and efficiency of human decision-making. In this chapter, we show that the computations of model-free reinforcement learning (RL) can in fact account for complex ...
openaire   +3 more sources

Memory and Resting‐State Connectivity in Acute Transient Global Amnesia: A Case–Control fMRI Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background and Objectives Transient global amnesia (TGA) is a striking model of isolated amnesia. While hippocampal lesions are well described, the network‐level mechanisms and the precise neuropsychological profile remain debated. Our objective was thus to characterize functional and neuropsychological correlates of acute TGA and their ...
Elias El Otmani, Emmanuel Barbeau, Béatrice Lemesle, Emilie Milongo‐Rigal, Sophie Fernandez, Sandrine Charpentier, Jean‐François Albucher, Nicolas Raposo, Fabrice Bonneville, Patrice Péran, Jérémie Pariente   +10 more
wiley   +1 more source

Learning Bayesian networks based on bi-velocity discrete particle swarm optimization with mutation operator

Open Mathematics, 2018
The problem of structures learning in Bayesian networks is to discover a directed acyclic graph that in some sense is the best representation of the given database. Score-based learning algorithm is one of the important structure learning methods used to
Wang Jingyun, Liu Sanyang
doaj   +1 more source

Robust Learning of Fixed-Structure Bayesian Networks

, 2018
We investigate the problem of learning Bayesian networks in a robust model where an $\epsilon$-fraction of the samples are adversarially corrupted. In this work, we study the fully observable discrete case where the structure of the network is given ...
Cheng, Yu, Diakonikolas, Ilias, Kane, Daniel, Stewart, Alistair   +3 more
core  

Spatial and Volumetric Characteristics of Glioblastoma: Associations With Clinical Presentation and Survival

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective We aim to comprehensively analyze how regional tumor and edema characteristics are associated with clinical presentations and survival outcomes in a large cohort of glioblastoma patients. Methods Patients with IDH‐wildtype glioblastoma who received brain MRI from 2010 to 2023 were included.
Daniel J. Zhou, Marc Jaskir, Julian Gal, Yombe Fonkeu, Christos Davatzikos, MacLean P. Nasrallah, Jose Garcia, Stephen J. Bagley, Arati Desai, Richard E. Phillips, Steven Tobochnik, Colin A. Ellis, James J. Gugger, Nishant Sinha, Joel M. Stein, Kathryn A. Davis   +15 more
wiley   +1 more source

From pixels to planning: scale-free active inference

Frontiers in Network Physiology
This paper describes a discrete state-space model and accompanying methods for generative modeling. This model generalizes partially observed Markov decision processes to include paths as latent variables, rendering it suitable for active inference and ...
Karl Friston, Karl Friston, Conor Heins, Tim Verbelen, Lancelot Da Costa, Lancelot Da Costa, Tommaso Salvatori, Dimitrije Markovic, Dimitrije Markovic, Alexander Tschantz, Magnus Koudahl, Christopher Buckley, Christopher Buckley, Thomas Parr   +13 more
doaj   +1 more source

Neural structure mapping in human probabilistic reward learning

eLife, 2019
Humans can learn abstract concepts that describe invariances over relational patterns in data. One such concept, known as magnitude, allows stimuli to be compactly represented on a single dimension (i.e. on a mental line).
Fabrice Luyckx, Hamed Nili, Bernhard Spitzer, Christopher Summerfield   +3 more
doaj   +1 more source