Zobrazeno 1 - 10
of 20 908
pro vyhledávání: '"A. Rajaram"'
Co-optimizing placement with congestion is integral to achieving high-quality designs. This paper presents GOALPlace, a new learning-based general approach to improving placement congestion by controlling cell density. Our method efficiently learns f
Externí odkaz:
http://arxiv.org/abs/2407.04579
Aperture synthesis observations with full polarisation have long been used to study the magnetic fields of synchrotron emitting sources. Recently proposed closure invariants give us a powerful method for extracting information from measured visibilit
Externí odkaz:
http://arxiv.org/abs/2407.00583
Autor:
Jasti, Jay, Zhong, Hua, Panwar, Vandana, Jarmale, Vipul, Miyata, Jeffrey, Carrillo, Deyssy, Christie, Alana, Rakheja, Dinesh, Modrusan, Zora, Kadel III, Edward Ernest, Beig, Niha, Huseni, Mahrukh, Brugarolas, James, Kapur, Payal, Rajaram, Satwik
Predictive biomarkers of treatment response are lacking for metastatic clear cell renal cell carcinoma (ccRCC), a tumor type that is treated with angiogenesis inhibitors, immune checkpoint inhibitors, mTOR inhibitors and a HIF2 inhibitor. The Angiosc
Externí odkaz:
http://arxiv.org/abs/2405.18327
Autor:
Shaham, Tamar Rott, Schwettmann, Sarah, Wang, Franklin, Rajaram, Achyuta, Hernandez, Evan, Andreas, Jacob, Torralba, Antonio
This paper describes MAIA, a Multimodal Automated Interpretability Agent. MAIA is a system that uses neural models to automate neural model understanding tasks like feature interpretation and failure mode discovery. It equips a pre-trained vision-lan
Externí odkaz:
http://arxiv.org/abs/2404.14394
To date, most discoveries of network subcomponents that implement human-interpretable computations in deep vision models have involved close study of single units and large amounts of human labor. We explore scalable methods for extracting the subgra
Externí odkaz:
http://arxiv.org/abs/2404.14349
Autor:
Mishra, Manit, Braham, Abderrahman, Marsom, Charles, Chung, Bryan, Griffin, Gavin, Sidnerlikar, Dakshesh, Sarin, Chatanya, Rajaram, Arjun
Conventional processes for analyzing datasets and extracting meaningful information are often time-consuming and laborious. Previous work has identified manual, repetitive coding and data collection as major obstacles that hinder data scientists from
Externí odkaz:
http://arxiv.org/abs/2404.00188
Autor:
Rajaram, Shwetha, Numan, Nels, Kumaravel, Balasaravanan Thoravi, Marquardt, Nicolai, Wilson, Andrew D.
Today's video-conferencing tools support a rich range of professional and social activities, but their generic, grid-based environments cannot be easily adapted to meet the varying needs of distributed collaborators. To enable end-user customization,
Externí odkaz:
http://arxiv.org/abs/2403.13947
Publikováno v:
The 33rd International Symposium on High-Performance Parallel and Distributed Computing (HPDC '24), June 3-7, 2024, Pisa, Italy. ACM, New York, NY, USA, 14 pages
Large language models are increasingly becoming a popular tool for software development. Their ability to model and generate source code has been demonstrated in a variety of contexts, including code completion, summarization, translation, and lookup
Externí odkaz:
http://arxiv.org/abs/2401.12554
This study introduces an innovative approach aimed at the efficient pruning of neural networks, with a particular focus on their deployment on edge devices. Our method involves the integration of the Lottery Ticket Hypothesis (LTH) with the Knowledge
Externí odkaz:
http://arxiv.org/abs/2401.10484
Autor:
The MICE Collaboration, Bogomilov, M., Tsenov, R., Vankova-Kirilova, G., Song, Y. P., Tang, J. Y., Li, Z. H., Bertoni, R., Bonesini, M., Chignoli, F., Mazza, R., de Bari, A., Orestano, D., Tortora, L., Kuno, Y., Sakamoto, H., Sato, A., Ishimoto, S., Chung, M., Sung, C. K., Filthaut, F., Fedorov, M., Jokovic, D., Maletic, D., Savic, M., Jovancevic, N., Nikolov, J., Vretenar, M., Ramberger, S., Asfandiyarov, R., Blondel, A., Drielsma, F., Karadzhov, Y., Boyd, S., Greis, J. R., Lord, T., Pidcott, C., Taylor, I., Charnley, G., Collomb, N., Dumbell, K., Gallagher, A., Grant, A., Griffiths, S., Hartnett, T., Martlew, B., Moss, A., Muir, A., Mullacrane, I., Oates, A., Owens, P., Stokes, G., Warburton, P., White, C., Adams, D., Bayliss, V., Boehm, J., Bradshaw, T. W., Brown, C., Courthold, M., Govans, J., Hayler, T., Hills, M., Lagrange, J. B., Macwaters, C., Nichols, A., Preece, R., Ricciardi, S., Rogers, C., Stanley, T., Tarrant, J., Tucker, M., Watson, S., Wilson, A., Bayes, R., Nugent, J. C., Soler, F. J. P., Chatzitheodoridis, G. T., Dick, A. J., Ronald, K., Whyte, C. G., Young, A. R., Gamet, R., Cooke, P., Blackmore, V. J., Colling, D., Dobbs, A., Dornan, P., Franchini, P., Hunt, C., Jurj, P. B., Kurup, A., Long, K., Martyniak, J., Middleton, S., Pasternak, J., Uchida, M. A., Cobb, J. H., Booth, C. N., Hodgson, P., Langlands, J., Overton, E., Pec, V., Smith, P. J., Wilbur, S., Ellis, M., Gardener, R. B. S., Kyberd, P., Nebrensky, J. J., DeMello, A., Gourlay, S., Lambert, A., Li, D., Luo, T., Prestemon, S., Virostek, S., Palmer, M., Witte, H., Adey, D., Bross, A. D., Bowring, D., Liu, A., Neuffer, D., Popovic, M., Rubinov, P., Freemire, B., Hanlet, P., Kaplan, D. M., Mohayai, T. A., Rajaram, D., Snopok, P., Torun, Y., Cremaldi, L. M., Sanders, D. A., Coney, L. R., Hanson, G. G., Heidt, C.
Accelerated muon beams have been considered for next-generation studies of high-energy lepton-antilepton collisions and neutrino oscillations. However, high-brightness muon beams have not yet been produced. The main challenge for muon acceleration an
Externí odkaz:
http://arxiv.org/abs/2310.05669