Zobrazeno 1 - 10
of 3 159
pro vyhledávání: '"Shirani P"'
Accurate estimation of treatment effects is essential for decision-making across various scientific fields. This task, however, becomes challenging in areas like social sciences and online marketplaces, where treating one experimental unit can influe
Externí odkaz:
http://arxiv.org/abs/2411.00945
Autor:
Chen, Zhuomin, Ni, Jingchao, Salehi, Hojat Allah, Zheng, Xu, Schafir, Esteban, Shirani, Farhad, Luo, Dongsheng
Graph representation learning (GRL), enhanced by graph augmentation methods, has emerged as an effective technique achieving performance improvements in wide tasks such as node classification and graph classification. In self-supervised GRL, paired g
Externí odkaz:
http://arxiv.org/abs/2410.12657
Heart and lung sounds are crucial for healthcare monitoring. Recent improvements in stethoscope technology have made it possible to capture patient sounds with enhanced precision. In this dataset, we used a digital stethoscope to capture both heart a
Externí odkaz:
http://arxiv.org/abs/2410.03280
Autor:
Zheng, Xu, Shirani, Farhad, Chen, Zhuomin, Lin, Chaohao, Cheng, Wei, Guo, Wenbo, Luo, Dongsheng
Recent research has developed a number of eXplainable AI (XAI) techniques. Although extracting meaningful insights from deep learning models, how to properly evaluate these XAI methods remains an open problem. The most widely used approach is to pert
Externí odkaz:
http://arxiv.org/abs/2410.02970
Federated learning (FL) has emerged as a promising framework for distributed machine learning. It enables collaborative learning among multiple clients, utilizing distributed data and computing resources. However, FL faces challenges in balancing pri
Externí odkaz:
http://arxiv.org/abs/2409.13133
We study the problem of system identification for stochastic continuous-time dynamics, based on a single finite-length state trajectory. We present a method for estimating the possibly unstable open-loop matrix by employing properly randomized contro
Externí odkaz:
http://arxiv.org/abs/2409.11327
This paper presents a comprehensive review of cardiorespiratory auscultation sensing devices which is useful for understanding the theoretical aspects of sensing devices, as well as practical notes to design novel sensing devices. One of the methods
Externí odkaz:
http://arxiv.org/abs/2406.12432
Speech in-painting is the task of regenerating missing audio contents using reliable context information. Despite various recent studies in multi-modal perception of audio in-painting, there is still a need for an effective infusion of visual and aud
Externí odkaz:
http://arxiv.org/abs/2406.01321
The process of reconstructing missing parts of speech audio from context is called speech in-painting. Human perception of speech is inherently multi-modal, involving both audio and visual (AV) cues. In this paper, we introduce and study a sequence-t
Externí odkaz:
http://arxiv.org/abs/2406.00901
Autor:
Liu, Zichuan, Wang, Tianchun, Shi, Jimeng, Zheng, Xu, Chen, Zhuomin, Song, Lei, Dong, Wenqian, Obeysekera, Jayantha, Shirani, Farhad, Luo, Dongsheng
Explaining deep learning models operating on time series data is crucial in various applications of interest which require interpretable and transparent insights from time series signals. In this work, we investigate this problem from an information
Externí odkaz:
http://arxiv.org/abs/2405.09308