Supporting human-agent communication for explainable planning in spatial-temporal planning problems [0.03%]
支持时空规划问题中可解释规划的人机通信
Alan Lindsay,Andrés A Ramírez-Duque,Bart Craenen et al.
Alan Lindsay et al.
The task of supporting a human operator to understand generated plans, and to explore the plan space, are important problems in automated planning. In this work, we consider the problem of plan explainability and plan space exploration in u...
Contrastive learning-based video quality assessment-jointed video vision transformer for video recognition [0.03%]
基于对比学习的视频质量评估联合视频视觉变换器用于视频识别
Jian Sun,Mohammad Mahoor
Jian Sun
Video quality significantly affects video classification. We found this problem when we classified Mild Cognitive Impairment well from clear videos, but worse from blurred ones. From then, we realized that referring to Video Quality Assessm...
Sequential pattern transformer (SPT): a generative and interpretable framework for predicting disease trajectories [0.03%]
序列模式变压器（SPT）：一种生成式和可解释的疾病轨迹预测框架
Mohammad Assadi Shalmani,Masoud Khani,Amirsajjad Taleban et al.
Mohammad Assadi Shalmani et al.
The effective integration of artificial intelligence into clinical workflows requires models that go beyond simple prediction to generate comprehensive, explainable, and actionable disease trajectories. Addressing the limitations of opaque ...
Balancing misclassification errors in image-based inference using problem domain semantics and a nested cascade architecture [0.03%]
基于问题领域的语义和嵌套级联体系结构的图像基推理中的误分类平衡方法
Xin Du,Rajesh Jena,Katayoun Farrahi et al.
Xin Du et al.
Pattern recognition models, particularly neural networks, often focus on maximising classification accuracy. However, in practice, the types of errors made (misclassification between different classes) can have varying associated costs. Cur...
Deep multi-objective reinforcement learning for utility-based infrastructural maintenance optimization [0.03%]
基于效用的基础设施维护优化的深度多目标强化学习
Jesse van Remmerden,Maurice Kenter,Diederik M Roijers et al.
Jesse van Remmerden et al.
In this paper, we introduce multi-objective deep centralized multi-agent actor-critic (MO-DCMAC), a multi-objective reinforcement learning method for infrastructural maintenance optimization, an area traditionally dominated by single-object...
A fairness scale for real-time recidivism forecasts using a national database of convicted offenders [0.03%]
基于全国罪犯数据库的实时再犯罪预测公平性尺度研究
Jacob Verrey,Peter Neyroud,Lawrence Sherman et al.
Jacob Verrey et al.
This investigation explores whether machine learning can predict recidivism while addressing societal biases. To investigate this, we obtained conviction data from the UK's Police National Computer (PNC) on 346,685 records between January 1...
Gene expression clock: an unsupervised deep learning approach for predicting circadian rhythmicity from whole genome expression [0.03%]
基因表达钟：一种预测全基因组表达昼夜节律的无监督深度学习方法
Aram Ansary Ogholbake,Qiang Cheng
Aram Ansary Ogholbake
Circadian rhythms are driven by an internal molecular clock which controls physiological and behavioral processes. Disruptions in these rhythms have been associated with health issues. Therefore, studying circadian rhythms is crucial for un...
Learning in public goods games: the effects of uncertainty and communication on cooperation [0.03%]
不确定性和沟通对公共物品博弈中合作影响的实验研究
Nicole Orzan,Erman Acar,Davide Grossi et al.
Nicole Orzan et al.
Communication is a widely used mechanism to promote cooperation in multi-agent systems. In the field of emergent communication, agents are typically trained in specific environments: cooperative, competitive or mixed-motive. Motivated by th...
Anna Penzkofer,Simon Schaefer,Florian Strohm et al.
Anna Penzkofer et al.
While deep reinforcement learning (RL) agents outperform humans on an increasing number of tasks, training them requires data equivalent to decades of human gameplay. Recent hierarchical RL methods have increased sample efficiency by incorp...
Fourier convolutional decoder: reconstructing solar flare images via deep learning [0.03%]
傅立叶卷积解码器——通过深度学习重建太阳耀斑图像
Merve Selcuk-Simsek,Paolo Massa,Hualin Xiao et al.
Merve Selcuk-Simsek et al.
Reconstructing images from observational data is a complex and time-consuming process, particularly in astronomy, where traditional algorithms like CLEAN require extensive computational resources and expert interpretation to distinguish gen...