Zobrazeno 1 - 10
of 26 150
pro vyhledávání: '"A, Seidman"'
Most existing generative models are limited to learning a single probability distribution from the training data and cannot generalize to novel distributions for unseen data. An architecture that can generate samples from both trained datasets and un
Externí odkaz:
http://arxiv.org/abs/2410.08549
Autor:
Adderley, P. A., Ahmed, S., Allison, T., Bachimanchi, R., Baggett, K., BastaniNejad, M., Bevins, B., Bevins, M., Bickley, M., Bodenstein, R. M., Bogacz, S. A., Bruker, M., Burrill, A., Cardman, L., Creel, J., Chao, Y. -C., Cheng, G., Ciovati, G., Chattopadhyay, S., Clark, J., Clemens, W. A., Croke, G., Daly, E., Davis, G. K., Delayen, J., De Silva, S. U., Dickson, R., Diaz, M., Drury, M., Doolittle, L., Douglas, D., Feldl, E., Fischer, J., Freyberger, A., Ganni, V., Geng, R. L., Ginsburg, C., Gomez, J., Grames, J., Gubeli, J., Guo, J., Hannon, F., Hansknecht, J., Harwood, L., Henry, J., Hernandez-Garcia, C., Higgins, S., Higinbotham, D., Hofler, A. S., Hiatt, T., Hogan, J., Hovater, C., Hutton, A., Jones, C., Jordan, K., Joyce, M., Kazimi, R., Keesee, M., Kelley, M. J., Keppel, C., Kimber, A., King, L., Kjeldsen, P., Kneisel, P., Koval, J., Krafft, G. A., Lahti, G., Larrieu, T., Lauze, R., Leemann, C., Legg, R., Li, R., Lin, F., Machie, D., Mammosser, J., Macha, K., Mahoney, K., Marhauser, F., Mastracci, B., Matalevich, J., McCarter, J., McCaughan, M., Merminga, L., Michaud, R., Morozov, V., Mounts, C., Musson, J., Nelson, R., Oren, W., Overton, R. B., Palacios-Serrano, G., Park, H. -K., Phillips, L., Philip, S., Pilat, F., Plawski, T., Poelker, M., Powers, P., Powers, T., Preble, J., Reilly, T., Rimmer, R., Reece, C., Robertson, H., Roblin, Y., Rode, C., Satogata, T., Seidman, D. J., Seryi, A., Shabalina, A., Shin, I., Slominski, R., Slominski, C., Spata, M., Spell, D., Spradlin, J., Stirbet, M., Stutzman, M. L., Suhring, S., Surles-Law, K., Suleiman, R., Tennant, C., Tian, H., Turner, D., Tiefenback, M., Trofimova, O., Valente, A. -M., Wang, H., Wang, Y., White, K., Whitlatch, C., Whitlatch, T., Wiseman, M., Wissman, M. J., Wu, G., Yang, S., Yunn, B., Zhang, S., Zhang, Y.
Publikováno v:
Phys. Rev. Accel. Beams 27 (2024) 084802
This review paper describes the energy-upgraded CEBAF accelerator. This superconducting linac has achieved 12 GeV beam energy by adding 11 new high-performance cryomodules containing eighty-eight superconducting cavities that have operated CW at an a
Externí odkaz:
http://arxiv.org/abs/2408.16880
Autor:
Refael, Yehonathan, Hakim, Adam, Greenberg, Lev, Aviv, Tal, Lokam, Satya, Fishman, Ben, Seidman, Shachar
Large language models (LLMs) have recently seen widespread adoption, in both academia and industry. As these models grow, they become valuable intellectual property (IP), reflecting enormous investments by their owners. Moreover, the high cost of clo
Externí odkaz:
http://arxiv.org/abs/2407.10886
TThe effects of alloying elements on diffusion pathways and migration energies of interstitial carbon in austenite (f.c.c.) and ferrite (b.c.c.) are studied using density functional theory first-principles calculations. The binding energies between c
Externí odkaz:
http://arxiv.org/abs/2405.18736
Autor:
Wang, Sifan, Seidman, Jacob H, Sankaran, Shyam, Wang, Hanwen, Pappas, George J., Perdikaris, Paris
Operator learning, which aims to approximate maps between infinite-dimensional function spaces, is an important area in scientific machine learning with applications across various physical domains. Here we introduce the Continuous Vision Transformer
Externí odkaz:
http://arxiv.org/abs/2405.13998
Despite having advantageous superconducting properties, Nb3Sn superconducting radiofrequency (SRF) cavities still have practical challenges compared to Nb SRF cavities due to the brittle nature of Nb3Sn. Performance degradation can occur when a Nb3Sn
Externí odkaz:
http://arxiv.org/abs/2405.00211
Autor:
Leslie Gardner, Peggy Bylund, Sarah Robbins, Emma Holler, Fereshtehossadat Shojaei, Fatemehalsadat Shojaei, Mark Seidman, Richard J. Holden, Nicole R. Fowler, Ben Zarzaur, Cristina Barboi, Malaz Boustani
Publikováno v:
Trials, Vol 25, Iss 1, Pp 1-14 (2024)
Abstract Background Clinical trial success hinges on efficient participant recruitment and retention. However, slow accrual and attrition frequently hinder progress. To address these challenges, a novel dashboard tool with control charts has been dev
Externí odkaz:
https://doaj.org/article/fbbd8e1b59f2408494e68fee4b7e99b5
Autor:
Peter Kip, Thijs J. Sluiter, Michael R. MacArthur, Ming Tao, Nicky Kruit, Sarah J. Mitchell, Jonathan Jung, Sander Kooijman, Josh Gorham, Jonathan G. Seidman, Paul H. A. Quax, Julius L. Decano, Masanori Aikawa, C. Keith Ozaki, James R. Mitchell, Margreet R. de Vries
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-19 (2024)
Abstract Short-term preoperative methionine restriction (MetR) is a promising translatable strategy to mitigate surgical injury response. However, its application to improve post-interventional vascular remodeling remains underexplored. Here we find
Externí odkaz:
https://doaj.org/article/8f299f54c6294dc69d98482c052be4d7
Autor:
S. M. Chew, E. Ferraro, Y. Chen, A. V. Barrio, D. Kelly, S. Modi, A. D. Seidman, H. Wen, E. Brogi, M. Robson, C. T. Dang
Publikováno v:
npj Breast Cancer, Vol 10, Iss 1, Pp 1-6 (2024)
Abstract Patients with HER2(+) early breast cancer (EBC) receiving neoadjuvant systemic therapy (NAST) have poorer outcomes if they have residual disease (RD). We analyzed IDFS and brain metastasis (BM) rates in patients with HER2(+) EBC treated with
Externí odkaz:
https://doaj.org/article/2f233c27a1544e54bbb4ef8c7d538226
Autor:
Seidman, A., author, Seidman, R.B., author
Publikováno v:
Yearbook Law & Legal Practice in East Asia: 1997/1998. :1-21