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相关概念视频

Hindsight Biases01:12

Hindsight Biases

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Hindsight bias leads you to believe that the event you just experienced was predictable, even though it really wasn’t. In other words, you knew all along that things would turn out the way they did. Can you relate this to the phrase "Hindsight is 20/20" now? 
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Time-Series Graph00:54

Time-Series Graph

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A time-series graph is a line graph with repeated measurements taken at successive intervals of time. It is also called a time series chart. To construct a time-series graph, one must look at both pieces of a paired data set. The horizontal axis is used to plot the time increments, and the vertical axis is used to plot the values of the variable that one is measuring. By using the axes in this way, each point on the graph will correspond to time and a measured quantity. The points on the graph...
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Autobiographical Memory01:14

Autobiographical Memory

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Autobiographical memory is a unique type of episodic memory that involves recollecting personal life experiences. It allows individuals to remember significant events from their past, creating a narrative of their lives. One interesting phenomenon related to autobiographical memory is the reminiscence bump. This effect refers to the tendency of adults to recall more events from their second and third decades of life — typically between ages 10 to 30 — than from other periods. This...
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End Point Prediction: Gran Plot01:07

End Point Prediction: Gran Plot

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A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
For potentiometric titration, the Gran plot is created by plotting...
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Regression Toward the Mean01:52

Regression Toward the Mean

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Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
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Social Scripts02:10

Social Scripts

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People tend to know what behavior is expected of them in specific, familiar settings. A script is a person’s knowledge about the sequence of events expected in a specific setting (Schank & Abelson, 1977). Essentially, scripts are a particular kind of schema, one containing default values for the features within an event. In the restaurant example, the script's features include the props (e.g., tables, menu, food, and money), the roles to be played (e.g., customer and waiter),...
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相关实验视频

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Trajectory Data Analyses for Pedestrian Space-time Activity Study
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SMEMO:用于轨迹预测的社会记忆

Francesco Marchetti, Federico Becattini, Lorenzo Seidenari

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    概括
    此摘要是机器生成的。

    这项研究引入了一种具有工作记忆的新型神经网络,用于建模人类互动和预测未来的轨迹. 该方法有效地学习了代理运动之间的因果关系,在轨迹预测方面取得了最先进的结果.

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    相关实验视频

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    科学领域:

    • 人工智能的人工智能
    • 计算机视觉 计算机视觉
    • 机器人技术 机器人技术 机器人技术

    背景情况:

    • 人类互动的建模对于预测未来的行为至关重要,特别是在轨迹预测中.
    • 由于社会规则,个人运动会影响周围的代理人,例如避免碰撞和跟随群体.

    研究的目的:

    • 开发一种算法方法来建模随时间变化的人类互动.
    • 呈现一个带有工作内存的神经网络,用于在交互建模中增强数据处理.

    主要方法:

    • 使用神经网络与端到端可训练工作记忆来存储,更新和召回代理信息.
    • 处理交互建模作为数据处理任务.

    主要成果:

    • 拟议的方法证明了能够学习介质运动之间的可解释的因果关系的能力.
    • 在多个轨迹预测数据集上实现了最先进的性能.

    结论:

    • 带有工作记忆的神经网络为建模复杂的人类互动提供了有效的框架.
    • 这种方法通过捕捉动态代理关系来推进轨迹预测领域.