Zobrazeno 1 - 10
of 285 119
pro vyhledávání: '"Chiu AS"'
Autor:
Chiu, Shih-Kai, Lin, Yu-Shen
We construct special Lagrangian submanifolds in collapsing Calabi-Yau 3-folds fibered by K3 surfaces. As these 3-folds collapse, the special Lagrangians shrink to 1-dimensional graphs in the base, mirroring the conjectured tropicalization of holomorp
Externí odkaz:
http://arxiv.org/abs/2410.17662
Ptychography is a computational method of microscopy that recovers high-resolution transmission images of samples from a series of diffraction patterns. While conventional phase retrieval algorithms can iteratively recover the images, they require ov
Externí odkaz:
http://arxiv.org/abs/2410.17377
Autor:
Zhang, Mian, Yang, Xianjun, Zhang, Xinlu, Labrum, Travis, Chiu, Jamie C., Eack, Shaun M., Fang, Fei, Wang, William Yang, Chen, Zhiyu Zoey
There is a significant gap between patient needs and available mental health support today. In this paper, we aim to thoroughly examine the potential of using Large Language Models (LLMs) to assist professional psychotherapy. To this end, we propose
Externí odkaz:
http://arxiv.org/abs/2410.13218
Autor:
Chiu, Cheng-Li, Wang, Taige, Fan, Ruihua, Watanabe, Kenji, Taniguchi, Takashi, Liu, Xiaomeng, Zaletel, Michael P., Yazdani, Ali
Charge distribution offers a unique fingerprint of important properties of electronic systems, including dielectric response, charge ordering and charge fractionalization. We develop a new architecture for charge sensing in two-dimensional electronic
Externí odkaz:
http://arxiv.org/abs/2410.10961
This paper addresses the open problem of conducting change-point analysis for interval-valued time series data using the maximum likelihood estimation (MLE) framework. Motivated by financial time series, we analyze data that includes daily opening (O
Externí odkaz:
http://arxiv.org/abs/2410.09884
Autor:
Artis, E., Bulbul, E., Grandis, S., Ghirardini, V., Clerc, N., Seppi, R., Comparat, J., Cataneo, M., von der Linden, A., Bahar, Y. E., Balzer, F., Chiu, I., Gruen, D., Kleinebreil, F., Kluge, M., Krippendorf, S., Li, X., Liu, A., Malavasi, N., Merloni, A., Miyatake, H., Miyazaki, S., Nandra, K., Okabe, N., Pacaud, F., Predehl, P., Ramos-Ceja, M. E., Reiprich, T. H., Sanders, J. S., Schrabback, T., Zelmer, S., Zhang, X.
Beyond testing the current cosmological paradigm, cluster number counts can also be utilized to investigate the discrepancies currently affecting current cosmological measurements. In particular, cosmological studies based on cosmic shear and other l
Externí odkaz:
http://arxiv.org/abs/2410.09499
We introduce DeepSets Operator Networks (DeepOSets), an efficient, non-autoregressive neural network architecture for in-context operator learning. In-context learning allows a trained machine learning model to learn from a user prompt without furthe
Externí odkaz:
http://arxiv.org/abs/2410.09298
Autor:
Abel, C., Ayres, N. J., Ban, G., Bison, G., Bodek, K., Bondar, V., Bouillaud, T., Bowles, D. C., Caratsch, G. L., Chanel, E., Chen, W., Chiu, P. -J., Crawford, C., Dechenaux, B., Doorenbos, C. B., Emmenegger, S., Ferraris-Bouchez, L., Fertl, M., Flaux, P., Fratangelo, A., Goupillière, D., Griffith, W. C., Höhl, D., Kasprzak, M., Kirch, K., Kletzl, V., Komposch, S. V., Koss, P. A., Krempel, J., Lauss, B., Lefort, T., Lejuez, A., Li, R., Meier, M., Menu, J., Michielsen, K., Mullan, P., Mullins, A., Naviliat-Cuncic, O., Pais, D., Piegsa, F. M., Pignol, G., Quemener, G., Rawlik, M., Rebreyend, D., Rienaecker, I., Ries, D., Roccia, S., Rozpedzik, D., Schnabel, A., Schmidt-Wellenburg, P., Segarra, E. P., Severijns, N., Smith, C. A., Svirina, K., Tavakoli, R., Thorne, J., Touati, S., Vankeirsbilck, J., Virot, R., Voigt, J., Wursten, E., Yazdandoost, N., Zejma, J., Ziehl, N., Zsigmond, G.
We present a coil system designed to generate a highly uniform magnetic field for the n2EDM experiment at the Paul Scherrer Institute. It consists of a main $B_0$ coil and a set of auxiliary coils mounted on a cubic structure with a side length of 27
Externí odkaz:
http://arxiv.org/abs/2410.07914
The recent development of Video-based Large Language Models (VideoLLMs), has significantly advanced video summarization by aligning video features and, in some cases, audio features with Large Language Models (LLMs). Each of these VideoLLMs possesses
Externí odkaz:
http://arxiv.org/abs/2410.04511
As we increasingly seek guidance from LLMs for decision-making in daily life, many of these decisions are not clear-cut and depend significantly on the personal values and ethical standards of the users. We present DailyDilemmas, a dataset of 1,360 m
Externí odkaz:
http://arxiv.org/abs/2410.02683