Zobrazeno 1 - 10
of 16 532
pro vyhledávání: '"Lin, Ming"'
Autor:
Driver, Taran, Guo, Zhaoheng, Isele, Erik, Grell, Gilbert, Ruberti, Marco, ONeal, Jordan T., Alexander, Oliver, Beauvarlet, Sandra, Cesar, David, Duris, Joseph, Garratt, Douglas, Larsen, Kirk A., Li, Siqi, Kolorenč, Přemysl, McCracken, Gregory A., Tuthill, Daniel, Wang, Zifan, Berrah, Nora, Bostedt, Christoph, Borne, Kurtis, Cheng, Xinxin, DiMauro, Louis F., Doumy, Gilles, Franz, Paris L., Kamalov, Andrei, Li, Xiang, Lin, Ming-Fu, Obaid, Razib, Picón, Antonio, Robles, River R., Rolles, Daniel, Rudenko, Artem, Shaikh, Moniruzzaman, Slaughter, Daniel S., Sudar, Nicholas S., Thierstein, Emily, Ueda, Kiyoshi, Wang, Enliang, Wang, Anna L., Weber, Thorsten, Wolf, Thomas J. A., Young, Linda, Zhang, Zhen, Averbukh, Vitali, Gessner, Oliver, Bucksbaum, Philip H., Kling, Matthias F., Palacios, Alicia, Martín, Fernando, Marangos, Jon P., Walter, Peter, Marinelli, Agostino, Cryan, James P.
In molecular systems, the ultrafast motion of electrons initiates the process of chemical change. Tracking this electronic motion across molecules requires coupling attosecond time resolution to atomic-scale spatial sensitivity. In this work, we empl
Externí odkaz:
http://arxiv.org/abs/2411.01700
As industrial models and designs grow increasingly complex, the demand for optimal control of large-scale dynamical systems has significantly increased. However, traditional methods for optimal control incur significant overhead as problem dimensions
Externí odkaz:
http://arxiv.org/abs/2411.01391
Autor:
Shen, Xuan, Zhao, Pu, Gong, Yifan, Kong, Zhenglun, Zhan, Zheng, Wu, Yushu, Lin, Ming, Wu, Chao, Lin, Xue, Wang, Yanzhi
Large Language Models (LLMs) have long held sway in the realms of artificial intelligence research. Numerous efficient techniques, including weight pruning, quantization, and distillation, have been embraced to compress LLMs, targeting memory reducti
Externí odkaz:
http://arxiv.org/abs/2409.17372
The estimated Glomerular Filtration Rate (eGFR) is an essential indicator of kidney function in clinical practice. Although traditional equations and Machine Learning (ML) models using clinical and laboratory data can estimate eGFR, accurately predic
Externí odkaz:
http://arxiv.org/abs/2409.02530
Autor:
Guzelturk, Burak, Portner, Joshua, Ondry, Justin, Ghanbarzadeh, Samira, Tarantola, Mia, Jeong, Ahhyun, Field, Thomas, Chandler, Alicia M., Wieman, Eliza, Hopper, Thomas R., Watkins, Nicolas E., Yue, Jin, Cheng, Xinxin, Lin, Ming-Fu, Luo, Duan, Kramer, Patrick L., Shen, Xiaozhe, Reid, Alexander H., Borkiewicz, Olaf, Ruett, Uta, Zhang, Xiaoyi, Lindenberg, Aaron M., Ma, Jihong, Schaller, Richard, Talapin, Dmitri V., Cotts, Benjamin L.
Symmetry control is essential for realizing unconventional properties, such as ferroelectricity, nonlinear optical responses, and complex topological order, thus it holds promise for the design of emerging quantum and photonic systems. Nevertheless,
Externí odkaz:
http://arxiv.org/abs/2408.15464
3D-free meets 3D priors: Novel View Synthesis from a Single Image with Pretrained Diffusion Guidance
Recent 3D novel view synthesis (NVS) methods are limited to single-object-centric scenes and struggle with complex environments. They often require extensive 3D data for training, lacking generalization beyond the training distribution. Conversely, 3
Externí odkaz:
http://arxiv.org/abs/2408.06157
Autor:
Thalapanane, Sandeep, Kumar, Sandip Sharan Senthil, Peethambari, Guru Nandhan Appiya Dilipkumar, SriHari, Sourang, Zheng, Laura, Poveda, Julio, Lin, Ming C.
Data for training learning-enabled self-driving cars in the physical world are typically collected in a safe, normal environment. Such data distribution often engenders a strong bias towards safe driving, making self-driving cars unprepared when enco
Externí odkaz:
http://arxiv.org/abs/2407.09466
Autor:
Borne, Kurtis, ONeal, Jordan T, Wang, Jun, Isele, Erk, Obaid, Razib, Berrah, Nora, Cheng, Xinxin, Bucksbaum, Philip H, James, Justin, Kamalov, Andri, Larsen, Kirk A, Li, Xiang, Lin, Ming-Fu, Liu, Yusong, Marinelli, Agostino, Summers, Adam, Thierstein, Emily, Wolf, Thomas, Rolles, Daniel, Walter, Peter, Cryan, James P, Driver, Taran
We describe the design and performance of a magnetic bottle electron spectrometer~(MBES) for high-energy electron spectroscopy. Our design features a ${\sim2}$~m long electron drift tube and electrostatic retardation lens, achieving sub-electronvolt
Externí odkaz:
http://arxiv.org/abs/2406.13083
Vector fields are widely used to represent and model flows for many science and engineering applications. This paper introduces a novel neural network architecture for learning tangent vector fields that are intrinsically defined on manifold surfaces
Externí odkaz:
http://arxiv.org/abs/2406.09648
In trajectory forecasting tasks for traffic, future output trajectories can be computed by advancing the ego vehicle's state with predicted actions according to a kinematics model. By unrolling predicted trajectories via time integration and models o
Externí odkaz:
http://arxiv.org/abs/2406.01431