Zobrazeno 1 - 10
of 617
pro vyhledávání: '"CHEN, ALVIN"'
Autor:
Chen, Alvin Po-Chun, Srinivas, Dananjay, Barry, Alexandra, Seniw, Maksim, Pacheco, Maria Leonor
NLP-assisted solutions have gained considerable traction to support qualitative data analysis. However, there does not exist a unified evaluation framework that can account for the many different settings in which qualitative researchers may employ t
Externí odkaz:
http://arxiv.org/abs/2408.09030
Extensive research exists on the performance of large language models on logic-based tasks, whereas relatively little has been done on their ability to generate creative solutions on lateral thinking tasks. The BrainTeaser shared task tests lateral t
Externí odkaz:
http://arxiv.org/abs/2405.02517
In this paper, we present a first-order Stress-Hybrid Virtual Element Method (SH-VEM) on six-noded triangular meshes for linear plane elasticity. We adopt the Hellinger--Reissner variational principle to construct a weak equilibrium condition and a s
Externí odkaz:
http://arxiv.org/abs/2401.06280
Autor:
Chen, Li, Rubin, Jonathan, Ouyang, Jiahong, Balaraju, Naveen, Patil, Shubham, Mehanian, Courosh, Kulhare, Sourabh, Millin, Rachel, Gregory, Kenton W, Gregory, Cynthia R, Zhu, Meihua, Kessler, David O, Malia, Laurie, Dessie, Almaz, Rabiner, Joni, Coneybeare, Di, Shopsin, Bo, Hersh, Andrew, Madar, Cristian, Shupp, Jeffrey, Johnson, Laura S, Avila, Jacob, Dwyer, Kristin, Weimersheimer, Peter, Raju, Balasundar, Kruecker, Jochen, Chen, Alvin
Self-supervised learning (SSL) methods have shown promise for medical imaging applications by learning meaningful visual representations, even when the amount of labeled data is limited. Here, we extend state-of-the-art contrastive learning SSL metho
Externí odkaz:
http://arxiv.org/abs/2310.10689
Autor:
Ouyang, Jiahong, Chen, Li, Li, Gary Y., Balaraju, Naveen, Patil, Shubham, Mehanian, Courosh, Kulhare, Sourabh, Millin, Rachel, Gregory, Kenton W., Gregory, Cynthia R., Zhu, Meihua, Kessler, David O., Malia, Laurie, Dessie, Almaz, Rabiner, Joni, Coneybeare, Di, Shopsin, Bo, Hersh, Andrew, Madar, Cristian, Shupp, Jeffrey, Johnson, Laura S., Avila, Jacob, Dwyer, Kristin, Weimersheimer, Peter, Raju, Balasundar, Kruecker, Jochen, Chen, Alvin
Frame-by-frame annotation of bounding boxes by clinical experts is often required to train fully supervised object detection models on medical video data. We propose a method for improving object detection in medical videos through weak supervision f
Externí odkaz:
http://arxiv.org/abs/2308.04463
Autor:
Chen, Alvin, Sukumar, N.
In this paper, we propose a robust low-order stabilization-free virtual element method on quadrilateral meshes for linear elasticity that is based on the stress-hybrid principle. We refer to this approach as the Stress-Hybrid Virtual Element Method (
Externí odkaz:
http://arxiv.org/abs/2304.04941
Autor:
Chen, Alvin, Sukumar, N.
We present a higher order stabilization-free virtual element method applied to plane elasticity problems. We utilize a serendipity approach to reduce the total number of degrees of freedom from the corresponding high-order approximations. The well-po
Externí odkaz:
http://arxiv.org/abs/2210.02653
In this paper, we develop a predictive geometry control framework for jet-based additive manufacturing (AM) based on a physics-guided recurrent neural network (RNN) model. Because of its physically interpretable architecture, the model's parameters a
Externí odkaz:
http://arxiv.org/abs/2207.03556
Autor:
CHEN, ALVIN (AUTHOR) alvin.chen@hhs.se
Publikováno v:
Journal of Finance (John Wiley & Sons, Inc.). Oct2024, Vol. 79 Issue 5, p3497-3541. 45p.
Autor:
Chen, Alvin, Sukumar, N.
We present the construction and application of a first order stabilization-free virtual element method to problems in plane elasticity. Well-posedness and error estimates of the discrete problem are established. The method is assessed on a series of
Externí odkaz:
http://arxiv.org/abs/2202.10037