Zobrazeno 1 - 10
of 6 743
pro vyhledávání: '"As, Laney"'
Autor:
Alsaadi, Aymen, Hategan-Marandiuc, Mihael, Maheshwari, Ketan, Merzky, Andre, Titov, Mikhail, Turilli, Matteo, Wilke, Andreas, Wozniak, Justin M., Chard, Kyle, da Silva, Rafael Ferreira, Jha, Shantenu, Laney, Daniel
Exascale computers offer transformative capabilities to combine data-driven and learning-based approaches with traditional simulation applications to accelerate scientific discovery and insight. However, these software combinations and integrations a
Externí odkaz:
http://arxiv.org/abs/2411.10637
Autor:
Bechtle, Philip, Breton, Dominique, Canet, Carlos Orero, Desch, Klaus, Dreiner, Herbi, Freyermuth, Oliver, Gauld, Rhorry, Gruber, Markus, Gutiérrez, César Blanch, Hajjar, Hazem, Hamer, Matthias, Heinrichs, Jan-Eric, Irles, Adrian, Kaminski, Jochen, Klipphahn, Laney, Lupberger, Michael, Maalmi, Jihane, Pöschl, Roman, Richarz, Leonie, Schiffer, Tobias, Schwäbig, Patrick, Schürmann, Martin, Zerwas, Dirk
We present a proposal for a future light dark matter search experiment at the Electron Stretcher Accelerator ELSA in Bonn: Lohengrin. It employs the fixed-target missing momentum based technique for searching for dark-sector particles. The Lohengrin
Externí odkaz:
http://arxiv.org/abs/2410.10956
Autor:
Sun, Xingzhi, Xu, Charles, Rocha, João F., Liu, Chen, Hollander-Bodie, Benjamin, Goldman, Laney, DiStasio, Marcello, Perlmutter, Michael, Krishnaswamy, Smita
In many data-driven applications, higher-order relationships among multiple objects are essential in capturing complex interactions. Hypergraphs, which generalize graphs by allowing edges to connect any number of nodes, provide a flexible and powerfu
Externí odkaz:
http://arxiv.org/abs/2409.09469
Autor:
Turilli, Matteo, Hategan-Marandiuc, Mihael, Titov, Mikhail, Maheshwari, Ketan, Alsaadi, Aymen, Merzky, Andre, Arambula, Ramon, Zakharchanka, Mikhail, Cowan, Matt, Wozniak, Justin M., Wilke, Andreas, Kilic, Ozgur Ozan, Chard, Kyle, da Silva, Rafael Ferreira, Jha, Shantenu, Laney, Daniel
Scientific discovery increasingly requires executing heterogeneous scientific workflows on high-performance computing (HPC) platforms. Heterogeneous workflows contain different types of tasks (e.g., simulation, analysis, and learning) that need to be
Externí odkaz:
http://arxiv.org/abs/2407.16646
Autor:
Titov, Mikhail, Carson, Robert, Rolchigo, Matthew, Coleman, John, Belak, James, Bement, Matthew, Laney, Daniel, Turilli, Matteo, Jha, Shantenu
When running at scale, modern scientific workflows require middleware to handle allocated resources, distribute computing payloads and guarantee a resilient execution. While individual steps might not require sophisticated control methods, bringing t
Externí odkaz:
http://arxiv.org/abs/2407.01484
Autor:
Chen, Ziyang, Gebru, Israel D., Richardt, Christian, Kumar, Anurag, Laney, William, Owens, Andrew, Richard, Alexander
We present a new dataset called Real Acoustic Fields (RAF) that captures real acoustic room data from multiple modalities. The dataset includes high-quality and densely captured room impulse response data paired with multi-view images, and precise 6D
Externí odkaz:
http://arxiv.org/abs/2403.18821
Autor:
Xu, Linning, Agrawal, Vasu, Laney, William, Garcia, Tony, Bansal, Aayush, Kim, Changil, Bulò, Samuel Rota, Porzi, Lorenzo, Kontschieder, Peter, Božič, Aljaž, Lin, Dahua, Zollhöfer, Michael, Richardt, Christian
We present an end-to-end system for the high-fidelity capture, model reconstruction, and real-time rendering of walkable spaces in virtual reality using neural radiance fields. To this end, we designed and built a custom multi-camera rig to densely c
Externí odkaz:
http://arxiv.org/abs/2311.02542
Autor:
Xu, Charles, Goldman, Laney, Guo, Valentina, Hollander-Bodie, Benjamin, Trank-Greene, Maedee, Adelstein, Ian, De Brouwer, Edward, Ying, Rex, Krishnaswamy, Smita, Perlmutter, Michael
Publikováno v:
Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4537-4545, 2024
Graph neural networks (GNNs) have emerged as a powerful tool for tasks such as node classification and graph classification. However, much less work has been done on signal classification, where the data consists of many functions (referred to as sig
Externí odkaz:
http://arxiv.org/abs/2310.17579
In this paper, we explore the potential of Large Language Models (LLMs) to reason about threats, generate information about tools, and automate cyber campaigns. We begin with a manual exploration of LLMs in supporting specific threat-related actions
Externí odkaz:
http://arxiv.org/abs/2310.06936
Autor:
Hategan-Marandiuc, Mihael, Merzky, Andre, Collier, Nicholson, Maheshwari, Ketan, Ozik, Jonathan, Turilli, Matteo, Wilke, Andreas, Wozniak, Justin M., Chard, Kyle, Foster, Ian, da Silva, Rafael Ferreira, Jha, Shantenu, Laney, Daniel
It is generally desirable for high-performance computing (HPC) applications to be portable between HPC systems, for example to make use of more performant hardware, make effective use of allocations, and to co-locate compute jobs with large datasets.
Externí odkaz:
http://arxiv.org/abs/2307.07895