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pro vyhledávání: '"Ghosh Debashis"'
Transformer models have demonstrated remarkable success in many domains such as natural language processing (NLP) and computer vision. With the growing interest in transformer-based architectures, they are now utilized for gesture recognition. So, we
Externí odkaz:
http://arxiv.org/abs/2411.07118
In this paper, we introduce a novel Multiscale Video Transformer Network (MVTN) for dynamic hand gesture recognition, since multiscale features can extract features with variable size, pose, and shape of hand which is a challenge in hand gesture reco
Externí odkaz:
http://arxiv.org/abs/2409.03890
Autor:
Gilbert, Peter B., Peng, James, Han, Larry, Lange, Theis, Lu, Yun, Nie, Lei, Shih, Mei-Chiung, Waddy, Salina P., Wiley, Ken, Yann, Margot, Zafari, Zafar, Ghosh, Debashis, Follmann, Dean, Juraska, Michal, Díaz, Iván
For many rare diseases with no approved preventive interventions, promising interventions exist, yet it has been difficult to conduct a pivotal phase 3 trial that could provide direct evidence demonstrating a beneficial effect on the target disease o
Externí odkaz:
http://arxiv.org/abs/2407.06350
Autor:
Ghosh Debashis, Cruz Cortés Efrén
Publikováno v:
Journal of Causal Inference, Vol 7, Iss 2, Pp 7353-60 (2019)
A powerful tool for the analysis of nonrandomized observational studies has been the potential outcomes model. Utilization of this framework allows analysts to estimate average treatment effects. This article considers the situation in which high-dim
Externí odkaz:
https://doaj.org/article/599ba7e0f70b442885c0227440466692
Transformer model have achieved state-of-the-art results in many applications like NLP, classification, etc. But their exploration in gesture recognition task is still limited. So, we propose a novel GestFormer architecture for dynamic hand gesture r
Externí odkaz:
http://arxiv.org/abs/2405.11180
Publikováno v:
Journal of Causal Inference, Vol 6, Iss 2, Pp 1-51 (2018)
An important goal in causal inference is to achieve balance in the covariates among the treatment groups. In this article, we introduce the concept of distributional balance preserving which requires the distribution of the covariates to be the same
Externí odkaz:
https://doaj.org/article/a89079e0a5484549abc9a2edcc8e9bb3
Ultra-high dimensional confounder selection algorithms comparison with application to radiomics data
Autor:
Baldé, Ismaïla, Ghosh, Debashis
Radiomics is an emerging area of medical imaging data analysis particularly for cancer. It involves the conversion of digital medical images into mineable ultra-high dimensional data. Machine learning algorithms are widely used in radiomics data anal
Externí odkaz:
http://arxiv.org/abs/2310.06315
Recognizing the importance of real-world data (RWD) for regulatory purposes, the United States (US) Congress passed the 21st Century Cures Act1 mandating the development of Food and Drug Administration (FDA) guidance on regulatory use of real-world e
Externí odkaz:
http://arxiv.org/abs/2310.03176
Publikováno v:
Journal of Causal Inference, Vol 3, Iss 1, Pp 25-40 (2015)
In this article, we study the causal inference problem with a continuous treatment variable using propensity score-based methods. For a continuous treatment, the generalized propensity score is defined as the conditional density of the treatment-leve
Externí odkaz:
https://doaj.org/article/d2ed925bc34d4eb6a62a710cb3929d56
Autor:
Dang, Lauren E, Gruber, Susan, Lee, Hana, Dahabreh, Issa, Stuart, Elizabeth A, Williamson, Brian D, Wyss, Richard, Díaz, Iván, Ghosh, Debashis, Kıcıman, Emre, Alemayehu, Demissie, Hoffman, Katherine L, Vossen, Carla Y, Huml, Raymond A, Ravn, Henrik, Kvist, Kajsa, Pratley, Richard, Shih, Mei-Chiung, Pennello, Gene, Martin, David, Waddy, Salina P, Barr, Charles E, Akacha, Mouna, Buse, John B, van der Laan, Mark, Petersen, Maya
Increasing emphasis on the use of real-world evidence (RWE) to support clinical policy and regulatory decision-making has led to a proliferation of guidance, advice, and frameworks from regulatory agencies, academia, professional societies, and indus
Externí odkaz:
http://arxiv.org/abs/2305.06850