Zobrazeno 1 - 10
of 2 891
pro vyhledávání: '"Luo, Rui"'
Adversarial attacks pose significant threats to the reliability and safety of deep learning models, especially in critical domains such as medical imaging. This paper introduces a novel framework that integrates conformal prediction with game-theoret
Externí odkaz:
http://arxiv.org/abs/2411.04376
Conformal inference is a statistical method used to construct prediction sets for point predictors, providing reliable uncertainty quantification with probability guarantees. This method utilizes historical labeled data to estimate the conformity or
Externí odkaz:
http://arxiv.org/abs/2411.01558
Autor:
Luo, Rui, Zhou, Zhixin
Uncertainty quantification is essential in decision-making, especially when joint distributions of random variables are involved. While conformal prediction provides distribution-free prediction sets with valid coverage guarantees, it traditionally f
Externí odkaz:
http://arxiv.org/abs/2408.10939
Autor:
Luo, Rui, Colombo, Nicolo
Conformal Prediction (CP) is a powerful framework for constructing prediction sets with guaranteed coverage. However, recent studies have shown that integrating confidence calibration with CP can lead to a degradation in efficiency. In this paper, We
Externí odkaz:
http://arxiv.org/abs/2407.17377
Autor:
Luo, Rui, Zhou, Zhixin
This paper introduces Conformal Thresholded Intervals (CTI), a novel conformal regression method that aims to produce the smallest possible prediction set with guaranteed coverage. Unlike existing methods that rely on nested conformal framework and f
Externí odkaz:
http://arxiv.org/abs/2407.14495
Autor:
Luo, Rui, Zhou, Zhixin
Conformal prediction is a powerful framework for constructing prediction sets with valid coverage guarantees in multi-class classification. However, existing methods often rely on a single score function, which can limit their efficiency and informat
Externí odkaz:
http://arxiv.org/abs/2407.10230
Autor:
Luo, Rui, Zhou, Zhixin
Machine learning classification tasks often benefit from predicting a set of possible labels with confidence scores to capture uncertainty. However, existing methods struggle with the high-dimensional nature of the data and the lack of well-calibrate
Externí odkaz:
http://arxiv.org/abs/2407.04407
Autor:
Liu, Yijia, Wang, Junzhi, Liu, Shu, Tang, Ningyu, Gong, Yan, Li, Yuqiang, LI, Juan, Luo, Rui, Xu, Yani
C$_4$H and $c$-C$_3$H$_2$, as unsaturated hydrocarbon molecules, are important for forming large organic molecules in the interstellar medium. We present mapping observations of C$_4$H ($N$=9$-8$) lines, $c$-C$_3$H$_2$ ($J_{Ka,Kb}$=2$_{1,2}$-1$_{0,1}
Externí odkaz:
http://arxiv.org/abs/2406.19740
Autor:
Wu, Ziwei, Zhu, Weiwei, Zhang, Bing, Feng, Yi, Han, JinLin, Li, Di, Li, Dongzi, Luo, Rui, Niu, Chenhui, Niu, Jiarui, Wang, Bojun, Wang, Fayin, Wang, Pei, Wang, Weiyang, Xu, Heng, Yang, Yuanpei, Zhang, Yongkun, Zhou, Dejiang, Zhu, Yuhao, Deng, Can-Min, Xu, Yonghua
We present the scintillation velocity measurements of FRB~20201124A from the FAST observations, which reveal an annual variation. This annual variation is further supported by changes detected in the scintillation arc as observed from the secondary s
Externí odkaz:
http://arxiv.org/abs/2406.12218
Autor:
Xu, Yani, Wang, Junzhi, Liu, Shu, Li, Juan, LI, Yuqiang, Luo, Rui, Ou, Chao, Zheng, Siqi, Liu, Yijia
Dense outflowing gas, traced by transitions of molecules with large dipole moment, is important for understanding mass loss and feedback of massive star formation. HCN 3-2 and HCO$^+$ 3-2 are good tracers of dense outflowing molecular gas, which are
Externí odkaz:
http://arxiv.org/abs/2406.08935