Zobrazeno 1 - 10
of 5 005
pro vyhledávání: '"Rusch, P."'
Autor:
Zhao, Jerry, Grubb, Daniel, Rusch, Miles, Wei, Tianrui, Anderson, Kevin, Nikolic, Borivoje, Asanovic, Krste
While the challenges and solutions for efficient execution of scalable vector ISAs on long-vector-length microarchitectures have been well established, not all of these solutions are suitable for short-vector-length implementations. This work propose
Externí odkaz:
http://arxiv.org/abs/2412.00997
Publikováno v:
Phys. Rev. E 110, 054606 (2024)
We analyze gravitaxis of a Brownian circle swimmer by deriving and characterizing analytically the experimentally measurable intermediate scattering function (ISF). To solve the associated Fokker-Planck equation we use a spectral-theory approach and
Externí odkaz:
http://arxiv.org/abs/2411.15192
Incorporating equivariance as an inductive bias into deep learning architectures to take advantage of the data symmetry has been successful in multiple applications, such as chemistry and dynamical systems. In particular, roto-translations are crucia
Externí odkaz:
http://arxiv.org/abs/2410.17878
Autor:
Rusch, T. Konstantin, Rus, Daniela
We propose Linear Oscillatory State-Space models (LinOSS) for efficiently learning on long sequences. Inspired by cortical dynamics of biological neural networks, we base our proposed LinOSS model on a system of forced harmonic oscillators. A stable
Externí odkaz:
http://arxiv.org/abs/2410.03943
Sampling-based motion planning methods, while effective in high-dimensional spaces, often suffer from inefficiencies due to irregular sampling distributions, leading to suboptimal exploration of the configuration space. In this paper, we propose an a
Externí odkaz:
http://arxiv.org/abs/2410.03909
Autor:
Hu, Yang, Lorenzin, Giacomo, Yeom, Jeyun, Liyanage, Manura, Curtin, William A., Jeurgens, Lars P. H., Janczak-Rusch, Jolanta, Cancellieri, Claudia, Turlo, Vladyslav
The intrinsic stress in nanomultilayers (NMLs) is typically dominated by interface stress, which is particularly high in immiscible Cu/W NMLs. Here, atomistic simulations with a chemically-accurate neural network potential reveal the role of interfac
Externí odkaz:
http://arxiv.org/abs/2406.14959
Discrepancy is a well-known measure for the irregularity of the distribution of a point set. Point sets with small discrepancy are called low-discrepancy and are known to efficiently fill the space in a uniform manner. Low-discrepancy points play a c
Externí odkaz:
http://arxiv.org/abs/2405.15059
Autor:
Omidi, Amir, Banawan, Mai, Weckenmann, Erwan, Paquin, Benoit, Geravand, Alireza, Zheng, Zibo, Shi, Wei, Zeng, Ming, Rusch, Leslie A.
We examine pulse amplitude modulation (PAM) for intensity modulation and direct detection systems. Using a straight-forward, mixed noise model, we optimize the constellations with an autoencoder-based neural network (NN), an improve required signal-t
Externí odkaz:
http://arxiv.org/abs/2402.04395
Publikováno v:
Physical Review E 109, 015303 (2024)
We investigate the usage of a recently introduced noise-cancellation algorithm for Brownian simulations to enhance the precision of measuring transport properties such as the mean-square displacement or the velocity-autocorrelation function. The algo
Externí odkaz:
http://arxiv.org/abs/2401.12577
Autor:
Lin, Zhongjin, Shastri, Bhavin J., Yu, Shangxuan, Song, Jingxiang, Zhu, Yuntao, Safarnejadian, Arman, Cai, Wangning, Lin, Yanmei, Ke, Wei, Hammood, Mustafa, Wang, Tianye, Xu, Mengyue, Zheng, Zibo, Al-Qadasi, Mohammed, Esmaeeli, Omid, Rahim, Mohamed, Pakulski, Grzegorz, Schmid, Jens, Barrios, Pedro, Jiang, Weihong, Morison, Hugh, Mitchell, Matthew, Guan, Xun, Jaeger, Nicolas A. F., Rusch, Leslie A. n, Shekhar, Sudip, Shi, Wei, Yu, Siyuan, Cai, Xinlun, Chrostowski, Lukas
Photonics offers a transformative approach to artificial intelligence (AI) and neuromorphic computing by enabling low-latency, high-speed, and energy-efficient computations. However, conventional photonic tensor cores face significant challenges in c
Externí odkaz:
http://arxiv.org/abs/2311.16896