| 1 |
An Explainable Deep Reinforcement Learning Model for Warfarin Maintenance Dosing Using Policy Distillation and Action Forging |
提出可解释的深度强化学习模型以优化华法林维持剂量 |
reinforcement learning deep reinforcement learning distillation |
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| 2 |
M3BAT: Unsupervised Domain Adaptation for Multimodal Mobile Sensing with Multi-Branch Adversarial Training |
提出M3BAT以解决多模态移动传感中的无监督领域适应问题 |
MAE multimodal |
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| 3 |
On the Road to Clarity: Exploring Explainable AI for World Models in a Driver Assistance System |
提出可解释AI方法以提升自动驾驶系统的透明度与安全性 |
world model world models |
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| 4 |
Probabilistic Inference in Language Models via Twisted Sequential Monte Carlo |
通过扭曲的序列蒙特卡洛方法实现语言模型的概率推断 |
reinforcement learning RLHF large language model |
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| 5 |
Knowledge Transfer for Cross-Domain Reinforcement Learning: A Systematic Review |
系统评估跨域强化学习中的知识转移方法 |
reinforcement learning |
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| 6 |
Using Neural Implicit Flow To Represent Latent Dynamics Of Canonical Systems |
提出神经隐式流以表示典型系统的潜在动态 |
latent dynamics |
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| 7 |
Tabular Data Contrastive Learning via Class-Conditioned and Feature-Correlation Based Augmentation |
提出基于类条件和特征相关性的对比学习方法以改进表格数据处理 |
contrastive learning |
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| 8 |
Online Policy Learning and Inference by Matrix Completion |
提出基于矩阵补全的在线策略学习与推断方法 |
policy learning |
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