Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Observational Learning01:12

Observational Learning

188
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...
188
Improving Translational Accuracy02:07

Improving Translational Accuracy

11.4K
Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
11.4K
Associative Learning01:27

Associative Learning

412
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...
412
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

110
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...
110
Propagation of Uncertainty from Systematic Error01:10

Propagation of Uncertainty from Systematic Error

534
The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...
534
Cognitive Learning01:21

Cognitive Learning

249
Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
249

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Neural regulation of cancer: from synaptic integration to neuro-immune regulation.

Cellular oncology (Dordrecht, Netherlands)·2026
Same author

Early melatonin supplementation partially delays gastrointestinal aging.

Biochimica et biophysica acta. Molecular basis of disease·2026
Same author

Kinetic Regulation of Anionic Redox Reaction Voltage by Metastable Over-Lithiated Surface Shells Formation for High-Energy-Density Batteries.

Angewandte Chemie (International ed. in English)·2026
Same author

Association between pre-pregnancy body mass index and neonatal outcomes in women undergoing assisted reproductive technology: a retrospective study.

BMC pregnancy and childbirth·2026
Same author

Zearalenone-14-glucoside forms a self-assembled supramolecular gel with enhanced toxicity through cytochrome P450 depletion.

Chemico-biological interactions·2026
Same author

Verbenone-based selenophene derivatives as potential anti-cancer agents: synthesis and biological evaluation in 2D and 3D A549 cell models.

RSC medicinal chemistry·2026
Same journal

Granular Ball-Based Noise-Resistant Fuzzy Multineighborhood Feature Selection via Label Enhancement and Feature Graph.

IEEE transactions on neural networks and learning systems·2026
Same journal

Fighting Evolving Spam With ARTMAP Models: A Noise-Resilient Online Detection Framework.

IEEE transactions on neural networks and learning systems·2026
Same journal

HyperSAT: Unsupervised Hypergraph Neural Networks for Weighted MaxSAT Problems.

IEEE transactions on neural networks and learning systems·2026
Same journal

Negation of Basic Belief Assignment in Multisource Information Fusion on Dempster-Shafer Theory With Applications in Pattern Classification.

IEEE transactions on neural networks and learning systems·2026
Same journal

Intervention Feasible Region and Driver Risk Capacity Aware Human-Machine Collaborative Safe Trajectory Planning.

IEEE transactions on neural networks and learning systems·2026
Same journal

A Unified Differential Denoising Learning Framework With a Pre-Trained Model and Fuzzy Graph Networks for Drug-Drug Interaction Prediction.

IEEE transactions on neural networks and learning systems·2026
查看所有相关文章

相关实验视频

Updated: Jul 12, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

599

对于噪音知识转移的双校正适应网络.

Yunyun Wang, Weiwen Zheng, Qinghao Li

    IEEE transactions on neural networks and learning systems
    |October 19, 2023
    PubMed
    概括
    此摘要是机器生成的。

    本研究介绍了DualCAN,这是一种用于无监督域调整的新型双向传输方法. 它使各个领域之间的相互学习成为可能,大大提高了对杂数据集的性能.

    更多相关视频

    Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
    06:37

    Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

    Published on: December 15, 2023

    3.8K
    Movement Retraining using Real-time Feedback of Performance
    08:16

    Movement Retraining using Real-time Feedback of Performance

    Published on: January 17, 2013

    13.4K

    相关实验视频

    Last Updated: Jul 12, 2025

    Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
    03:14

    Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

    Published on: December 6, 2024

    599
    Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
    06:37

    Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

    Published on: December 15, 2023

    3.8K
    Movement Retraining using Real-time Feedback of Performance
    08:16

    Movement Retraining using Real-time Feedback of Performance

    Published on: January 17, 2013

    13.4K

    科学领域:

    • 计算机科学 计算机科学
    • 人工智能的人工智能
    • 机器学习 机器学习

    背景情况:

    • 无监督域调整 (UDA) 通常使用从源域到目标域的单向传输.
    • 从目标到源的反向转移,对于良性学习周期至关重要,尚未得到充分探索.
    • 由于模型偏差和固有的域噪声,现有的方法在噪声放大方面扎.

    研究的目的:

    • 为无监督域调整引入一种新的双向转移方法.
    • 解决跨领域学习中的噪音放大问题.
    • 通过相互适应和纠正,增强源和目标领域的学习.

    主要方法:

    • 提出DualCAN (双校正适应网络) 的建议.
    • 在源域和目标域之间实施循环适应和纠正过程.
    • 利用目标领域的知识来完善源领域的适应,反之亦然.

    主要成果:

    • 在各种UDA任务中展示显著的绩效增长.
    • 在极其杂的数据集上实现实质性的改进,例如,Office-31上的+10%,标签腐败率为40%.
    • 验证双向转移和校正机制的有效性.

    结论:

    • 双CAN代表了UDA中双向适应的第一个尝试.
    • 拟议的方法有效地减轻噪音,并促进了这两个领域的学习.
    • 这种方法为强大和高效的域调整提供了一个有希望的方向.