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

Observational Learning01:12

Observational Learning

370
Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning...
370
Associative Learning01:27

Associative Learning

650
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...
650
Introduction to Learning01:18

Introduction to Learning

595
Learning is the process of acquiring knowledge or skills through practice or experience, leading to long-lasting behavioral changes. This acquisition occurs through interaction with the environment and requires practice or experience. For instance, mastering a skill such as surfing requires considerable practice and experience, highlighting the essential role of repeated interactions with the environment in learning.
In contrast to learned behaviors, unlearned behaviors such as crying, sexual...
595
Encoding01:19

Encoding

286
Information enters the brain through encoding, which is the input of information into the memory system. Once sensory information is received from the environment, the brain labels or codes it. The information is then organized with similar information and connected to existing concepts. Encoding occurs through automatic processing and effortful processing.
Automatic processing involves the encoding of details like time, space, frequency, and the meaning of words, usually done without conscious...
286
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

195
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
195
Perception01:28

Perception

651
Perception is a fundamental psychological process that enables individuals to organize, interpret, and consciously experience sensory information. This process is crucial for understanding and interacting with the world around us. It includes both bottom-up and top-down processing, each playing a distinct role in how we perceive our environment.
Bottom-up processing begins at the sensory level, where receptors detect external environmental stimuli. These could include the tactile sensation of...
651

You might also read

Related Articles

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

Sort by
Same author

Temporal dynamics of requirements engineering from mobile app reviews.

PeerJ. Computer science·2022
Same author

A network-based positive and unlabeled learning approach for fake news detection.

Machine learning·2021
See all related articles

Related Experiment Video

Updated: Oct 9, 2025

Decoding Natural Behavior from Neuroethological Embedding
08:00

Decoding Natural Behavior from Neuroethological Embedding

Published on: October 3, 2025

37

Learning to sense from events via semantic variational autoencoder.

Marcos Paulo Silva Gôlo1, Rafael Geraldeli Rossi2, Ricardo Marcondes Marcacini1

  • 1Institute of Mathematics and Computer Sciences, University of São Paulo, São Carlos, São Paulo, Brazil.

Plos One
|December 23, 2021
PubMed
Summary

This study introduces "learning to sense" to understand interdependent events using semantic vector spaces. A Semantic Variational Autoencoder (SVAE) effectively maps textual and spatio-temporal event data, improving event analysis and sensing capabilities.

More Related Videos

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment
08:25

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Published on: May 7, 2019

9.2K
Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.3K

Related Experiment Videos

Last Updated: Oct 9, 2025

Decoding Natural Behavior from Neuroethological Embedding
08:00

Decoding Natural Behavior from Neuroethological Embedding

Published on: October 3, 2025

37
Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment
08:25

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Published on: May 7, 2019

9.2K
Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.3K

Area of Science:

  • Artificial Intelligence
  • Machine Learning
  • Data Science

Background:

  • Human reasoning involves monitoring interdependent events for decision-making.
  • Event datasets combine textual data with spatio-temporal features.
  • Mapping related events in a semantic vector space is key for contextual understanding.

Purpose of the Study:

  • Introduce the concept of "learning to sense" to emulate human reasoning.
  • Address the challenge of creating semantic vector spaces for events that satisfy both textual and spatio-temporal constraints.
  • Investigate a Semantic Variational Autoencoder (SVAE) for event analysis and sensing.

Main Methods:

  • Developed a Semantic Variational Autoencoder (SVAE) model.
  • Fine-tuned pre-trained embeddings using textual and spatio-temporal event data.
  • Employed a one-class classification baseline for comparison.

Main Results:

  • The SVAE model demonstrated superior performance compared to the baseline.
  • Experiments involved over one hundred sensors.
  • The SVAE successfully mapped related events in a semantic vector space, considering both text and spatio-temporal data.

Conclusions:

  • The proposed SVAE is effective for learning to sense by integrating textual and spatio-temporal event information.
  • The SVAE provides valuable tools for sensing scenarios, including visualization of decision functions and geographic impact heat maps.
  • This approach enhances event analysis and decision-making processes in complex environments.