Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Generalization, Discrimination, and Extinction01:24

Generalization, Discrimination, and Extinction

451
Generalization, discrimination, and extinction are key concepts in operant conditioning that influence how behaviors are learned and maintained.
Generalization occurs when a behavior reinforced in one context is performed in similar situations. For instance, a student who studies diligently for calculus and receives excellent grades might apply the same study habits to psychology and history, expecting similar results. Generalization shows how learning in one setting can influence behavior in...
451
Cause and Effect01:53

Cause and Effect

10.9K
While variables are sometimes correlated because one does cause the other, it could also be that some other factor, a confounding variable, is actually causing the systematic movement in our variables of interest. For instance, as sales in ice cream increase, so does the overall rate of crime. Is it possible that indulging in your favorite flavor of ice cream could send you on a crime spree? Or, after committing crime do you think you might decide to treat yourself to a cone?
10.9K
Case Studies01:22

Case Studies

11.6K
There are many research methods available to psychologists in their efforts to understand, describe, and explain behavior and the cognitive and biological processes that underlie it.
11.6K
The Representativeness Heuristic02:13

The Representativeness Heuristic

15.8K
The representative heuristic describes a biased way of thinking, in which you unintentionally stereotype someone or something. For example, you may assume that your professors spend their free time reading books and engaging in intellectual conversation, because the idea of them spending their time playing volleyball or visiting an amusement park does not fit in with your stereotypes of professors.
15.8K
Associative Learning01:27

Associative Learning

300
Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
300
Multiple Bar Graph01:07

Multiple Bar Graph

5.1K
As the name suggests, a multiple bar graph is the same as a bar graph but has multiple bars to depict relationships between different data values. One can include as many parameters as possible. However, each parameter must have the same unit of measurement.
Each bar or column in the multiple bar graph represents a data value. These graphs are used primarily in interrelating two or more sets of data. The categories of different kinds of data are listed along the horizontal or x-axis, whereas...
5.1K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Revisiting deep information propagation: Fractal frontier and finite-size effects.

Neural networks : the official journal of the International Neural Network Society·2026
Same author

Cough acoustic analysis using artificial intelligence for COVID-19 detection: A comparative study of patient cohorts from Lima, Peru and Montreal, Canada.

Annals of epidemiology·2026
Same author

From Speech to Sonography: Spectral Networks for Ultrasound Microstructure Classification.

IEEE transactions on bio-medical engineering·2025
Same author

Development and Application of Children's Sex- and Age-Specific Fat-Mass and Muscle-Mass Reference Curves From Dual-Energy X-Ray Absorptiometry Data for Predicting Cardiometabolic Risk.

Pediatric obesity·2025
Same author

VC dimension of Graph Neural Networks with Pfaffian activation functions.

Neural networks : the official journal of the International Neural Network Society·2024
Same author

A protocol for trustworthy EEG decoding with neural networks.

Neural networks : the official journal of the International Neural Network Society·2024

Related Experiment Video

Updated: Jun 10, 2025

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques
08:05

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques

Published on: June 30, 2020

7.5K

Generalization limits of Graph Neural Networks in identity effects learning.

Giuseppe Alessio D'Inverno1, Simone Brugiapaglia2, Mirco Ravanelli3

  • 1DIISM - University of Siena, via Roma 56, Siena, 53100, Italy.

Neural Networks : the Official Journal of the International Neural Network Society
|October 19, 2024
PubMed
Summary

Graph Neural Networks (GNNs) struggle with identity tasks on unseen data, particularly with orthogonal encodings. However, their connection to the Weisfeiler-Lehman (WL) test offers positive results for specific graph structures.

Keywords:
Dicyclic graphsEncodingsGeneralizationGradient descentGraph Neural NetworksIdentity effects

More Related Videos

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception
05:48

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

Published on: August 9, 2024

1.4K
Experimental Paradigm for Measuring the Effect of Induced Emotion on Grammar Learning
05:33

Experimental Paradigm for Measuring the Effect of Induced Emotion on Grammar Learning

Published on: January 29, 2020

6.0K

Related Experiment Videos

Last Updated: Jun 10, 2025

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques
08:05

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques

Published on: June 30, 2020

7.5K
Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception
05:48

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

Published on: August 9, 2024

1.4K
Experimental Paradigm for Measuring the Effect of Induced Emotion on Grammar Learning
05:33

Experimental Paradigm for Measuring the Effect of Induced Emotion on Grammar Learning

Published on: January 29, 2020

6.0K

Area of Science:

  • Machine Learning
  • Graph Theory
  • Artificial Intelligence

Background:

  • Graph Neural Networks (GNNs) are powerful tools for graph data analysis, often utilizing message-passing mechanisms.
  • Their expressive power is linked to the Weisfeiler-Lehman (WL) test for graph isomorphism.
  • Understanding GNN generalization is crucial for applications in linguistics and chemistry.

Purpose of the Study:

  • To establish generalization properties and fundamental limits of GNNs for learning identity effects.
  • To investigate GNN capabilities in simple cognitive tasks.
  • To analyze performance on two-letter words and dicyclic graphs.

Main Methods:

  • Theoretical analysis of GNN generalization properties.
  • Case studies on two-letter words using orthogonal encodings (one-hot).
  • Analysis of dicyclic graphs leveraging the GNN-WL test connection.
  • Extensive numerical studies to support theoretical findings.

Main Results:

  • GNNs trained with stochastic gradient descent fail to generalize to unseen letters in two-letter word tasks with orthogonal encodings.
  • Positive existence results are demonstrated for GNNs on dicyclic graphs, utilizing the GNN-WL test equivalence.
  • The study reveals specific limitations and capabilities of GNNs in discerning identity effects.

Conclusions:

  • GNNs exhibit limitations in generalizing identity effects, especially with certain encoding methods and tasks.
  • The equivalence to the WL test provides a theoretical basis for understanding GNN performance on specific graph structures.
  • Further research is needed to enhance GNN generalization for cognitive tasks in computational linguistics and chemistry.