Results 231 to 240 of about 3,551,086 (288)

N170 Amplitude to Rare Neutral Faces in an Oddball Condition Reflects Prediction Error. [PDF]

Eur J Neurosci
Liu X, Li X, Astikainen P.
europepmc   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

International Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli, Marco Forgione, Dario Piga, Marco Zaffalon   +3 more
wiley   +1 more source

Maternal anxiety shapes prediction error responses in the infant brain. [PDF]

Neurophotonics
Billing ADN, Smith ES, Cooper RJ, Lawson RP.   +3 more
europepmc   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

Circuit-level modeling of prediction error computation of multi-dimensional features in voluntary actions. [PDF]

Front Comput Neurosci
Huang Y, Li Y.
europepmc   +1 more source

What Do Large Language Models Know About Materials?

Advanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source

The Anterior Insula Processes a Time-Resolved Subjective Risk Prediction Error. [PDF]

J Neurosci
Kim JC, Hellrung L, Nebe S, Tobler PN.
europepmc   +1 more source

Lateral habenula and periaqueductal gray neurons signal reward prediction error and continuity of reward expectancy to drive reward-seeking behavior. [PDF]

Cell Rep
Lee H, Hikosaka O.
europepmc   +1 more source

Altered amygdala and striatal responsivity and prediction error encoding of temporal reward dynamics in post-trauma psychopathology. [PDF]

Neuropsychopharmacology
Enten LK, DeMarco A, Kline R, Globisch FM, Dunsmoor JE, Cisler JM, Nemeroff CB, Fonzo GA.   +7 more
europepmc   +1 more source