Zobrazeno 1 - 10
of 15 903
pro vyhledávání: '"Chawla, P."'
Autor:
Mehonic, Adnan, Ielmini, Daniele, Roy, Kaushik, Mutlu, Onur, Kvatinsky, Shahar, Serrano-Gotarredona, Teresa, Linares-Barranco, Bernabe, Spiga, Sabina, Savelev, Sergey, Balanov, Alexander G, Chawla, Nitin, Desoli, Giuseppe, Malavena, Gerardo, Compagnoni, Christian Monzio, Wang, Zhongrui, Yang, J Joshua, Syed, Ghazi Sarwat, Sebastian, Abu, Mikolajick, Thomas, Noheda, Beatriz, Slesazeck, Stefan, Dieny, Bernard, Tuo-Hung, Hou, Varri, Akhil, Bruckerhoff-Pluckelmann, Frank, Pernice, Wolfram, Zhang, Xixiang, Pazos, Sebastian, Lanza, Mario, Wiefels, Stefan, Dittmann, Regina, Ng, Wing H, Buckwell, Mark, Cox, Horatio RJ, Mannion, Daniel J, Kenyon, Anthony J, Lu, Yingming, Yang, Yuchao, Querlioz, Damien, Hutin, Louis, Vianello, Elisa, Chowdhury, Sayeed Shafayet, Mannocci, Piergiulio, Cai, Yimao, Sun, Zhong, Pedretti, Giacomo, Strachan, John Paul, Strukov, Dmitri, Gallo, Manuel Le, Ambrogio, Stefano, Valov, Ilia, Waser, Rainer
The roadmap is organized into several thematic sections, outlining current computing challenges, discussing the neuromorphic computing approach, analyzing mature and currently utilized technologies, providing an overview of emerging technologies, add
Externí odkaz:
http://arxiv.org/abs/2407.02353
We embed the Penrose limit into the Weyl classical double copy. Thereby, we provide a lift of the double copy properties of plane wave spacetimes into black hole geometries and we open a novel avenue towards taking the classical double copy beyond st
Externí odkaz:
http://arxiv.org/abs/2406.14601
Autor:
Wornow, Michael, Narayan, Avanika, Viggiano, Ben, Khare, Ishan S., Verma, Tathagat, Thompson, Tibor, Hernandez, Miguel Angel Fuentes, Sundar, Sudharsan, Trujillo, Chloe, Chawla, Krrish, Lu, Rongfei, Shen, Justin, Nagaraj, Divya, Martinez, Joshua, Agrawal, Vardhan, Hudson, Althea, Shah, Nigam H., Re, Christopher
Existing ML benchmarks lack the depth and diversity of annotations needed for evaluating models on business process management (BPM) tasks. BPM is the practice of documenting, measuring, improving, and automating enterprise workflows. However, resear
Externí odkaz:
http://arxiv.org/abs/2406.13264
Autor:
Le, Khiem, Guo, Zhichun, Dong, Kaiwen, Huang, Xiaobao, Nan, Bozhao, Iyer, Roshni, Zhang, Xiangliang, Wiest, Olaf, Wang, Wei, Chawla, Nitesh V.
Recently, Large Language Models (LLMs) with their strong task-handling capabilities have shown remarkable advancements across a spectrum of fields, moving beyond natural language understanding. However, their proficiency within the chemistry domain r
Externí odkaz:
http://arxiv.org/abs/2406.06777
Autor:
Chawla, Palak, Shweta, Swain, K. R., Patel, Tushti, Bala, Renu, Shetty, Disha, Sugisaki, Kenji, Mandal, Sudhindu Bikash, Riu, Jordi, Nogue, Jan, Prasannaa, V. S., Das, B. P.
The quantum-classical hybrid Variational Quantum Eigensolver (VQE) algorithm is recognized to be the method of choice to obtain ground state energies of quantum many-body systems in the noisy intermediate scale quantum (NISQ) era. This study not only
Externí odkaz:
http://arxiv.org/abs/2406.04992
Protective applications require energy-absorbing materials that are soft and compressible enough to absorb kinetic energy from impacts, yet stiff enough to bear crushing loads. Achieving this balance requires careful consideration of both mechanical
Externí odkaz:
http://arxiv.org/abs/2406.04803
There are vast number of configurable parameters in a Radio Access Telecom Network. A significant amount of these parameters is configured by Radio Node or cell based on their deployment setting. Traditional methods rely on domain knowledge for indiv
Externí odkaz:
http://arxiv.org/abs/2406.04779
Autor:
Aalbers, J., Akerib, D. S., Musalhi, A. K. Al, Alder, F., Amarasinghe, C. S., Ames, A., Anderson, T. J., Angelides, N., Araújo, H. M., Armstrong, J. E., Arthurs, M., Baker, A., Balashov, S., Bang, J., Barillier, E. E., Bargemann, J. W., Beattie, K., Benson, T., Bhatti, A., Biekert, A., Biesiadzinski, T. P., Birch, H. J., Bishop, E. J., Blockinger, G. M., Boxer, B., Brew, C. A. J., Brás, P., Burdin, S., Buuck, M., Carmona-Benitez, M. C., Carter, M., Chawla, A., Chen, H., Cherwinka, J. J., Chin, Y. T., Chott, N. I., Converse, M. V., Cottle, A., Cox, G., Curran, D., Dahl, C. E., David, A., Delgaudio, J., Dey, S., deViveiros, L., DiFelice, L., Ding, C., Dobson, J. E. Y., Druszkiewicz, E., Eriksen, S. R., Fan, A., Fearon, N. M., Fiorucci, S., Flaecher, H., Fraser, E. D., Fruth, T. M. A., Gaitskell, R. J., Geffre, A., Genovesi, J., Ghag, C., Gibbons, R., Gokhale, S., Green, J., vanderGrinten, M. G. D., Haiston, J. J., Hall, C. R., Han, S., Hartigan-O'Connor, E., Haselschwardt, S. J., Hernandez, M. A., Hertel, S. A., Heuermann, G., Homenides, G. J., Horn, M., Huang, D. Q., Hunt, D., Jacquet, E., James, R. S., Johnson, J., Kaboth, A. C., Kamaha, A. C., Kannichankandy, M., Khaitan, D., Khazov, A., Khurana, I., DKim, J., Kim, J., Kingston, J., Kirk, R., Kodroff, D., Korley, L., Korolkova, E. V., Kraus, H., Kravitz, S., Kreczko, L., Kudryavtsev, V. A., Leonard, D. S., Lesko, K. T., Levy, C., Lin, J., Lindote, A., Linehan, R., Lippincott, W. H., Lopes, M. I., Lorenzon, W., Lu, C., Luitz, S., Majewski, P. A., Manalaysay, A., Mannino, R. L., Maupin, C., McCarthy, M. E., McDowell, G., McKinsey, D. N., McLaughlin, J., McLaughlin, J. B., McMonigle, R., Miller, E. H., Mizrachi, E., Monte, A., Monzani, M. E., Mendoza, J. D. Morales, Morrison, E., Mount, B. J., Murdy, M., Murphy, A. St. J., Naylor, A., Nelson, H. N., Neves, F., Nguyen, A., Nikoleyczik, J. A., Olcina, I., Oliver-Mallory, K. C., Orpwood, J., Palladino, K. J., Palmer, J., Pannifer, N. J., Parveen, N., Patton, S. J., Penning, B., Pereira, G., Perry, E., Pershing, T., Piepke, A., Qie, Y., Reichenbacher, J., Rhyne, C. A., Riffard, Q., Rischbieter, G. R. C., Riyat, H. S., Rosero, R., Rushton, T., Rynders, D., Santone, D., Sazzad, A. B. M. R., Schnee, R. W., Shaw, S., Shutt, T., Silk, J. J., Silva, C., Sinev, G., Siniscalco, J., Smith, R., Solovov, V. N., Sorensen, P., Soria, J., Stancu, I., Stevens, A., Stifter, K., Suerfu, B., Sumner, T. J., Szydagis, M., Taylor, W. C., Tiedt, D. R., Timalsina, M., Tong, Z., Tovey, D. R., Tranter, J., Trask, M., Tripathi, M., Tronstad, D. R., Vacheret, A., Vaitkus, A. C., Valentino, O., Velan, V., Wang, A., Wang, J. J., Wang, Y., Watson, J. R., Webb, R. C., Weeldreyer, L., Whitis, T. J., Williams, M., Wisniewski, W. J., Wolfs, F. L. H., Woodford, S., Woodward, D., Wright, C. J., Xia, Q., Xiang, X., Xu, J., Yeh, M., Zweig, E. A.
Weakly interacting massive particles (WIMPs) may interact with a virtual pion that is exchanged between nucleons. This interaction channel is important to consider in models where the spin-independent isoscalar channel is suppressed. Using data from
Externí odkaz:
http://arxiv.org/abs/2406.02441
A long-standing dilemma prevents the broader application of explanation methods: general applicability and inference speed. On the one hand, existing model-agnostic explanation methods usually make minimal pre-assumptions about the prediction models
Externí odkaz:
http://arxiv.org/abs/2405.18664
Despite being a heavily researched topic, Adversarial Training (AT) is rarely, if ever, deployed in practical AI systems for two primary reasons: (i) the gained robustness is frequently accompanied by a drop in generalization and (ii) generating adve
Externí odkaz:
http://arxiv.org/abs/2405.17130