Zobrazeno 1 - 10
of 3 198
pro vyhledávání: '"Kung, H."'
Autor:
Hsieh, He-Yen, Li, Ziyun, Zhang, Sai Qian, Ting, Wei-Te Mark, Chang, Kao-Den, De Salvo, Barbara, Liu, Chiao, Kung, H. T.
We present GazeGen, a user interaction system that generates visual content (images and videos) for locations indicated by the user's eye gaze. GazeGen allows intuitive manipulation of visual content by targeting regions of interest with gaze. Using
Externí odkaz:
http://arxiv.org/abs/2411.04335
Autor:
Farias, Matheus, Kung, H. T.
We introduce a novel approach to reduce the number of times required for reprogramming memristors on bit-sliced compute-in-memory crossbars for deep neural networks (DNNs). Our idea addresses the limited non-volatile memory endurance, which restrict
Externí odkaz:
http://arxiv.org/abs/2410.21730
Autor:
Farias, Matheus, Kung, H. T.
We introduce $\textit{sorted weight sectioning}$ (SWS): a weight allocation algorithm that places sorted deep neural network (DNN) weight sections on bit-sliced compute-in-memory (CIM) crossbars to reduce analog-to-digital converter (ADC) energy cons
Externí odkaz:
http://arxiv.org/abs/2410.11298
Autor:
Bannies, J., Michiardi, M., Kung, H. -H., Godin, S., Simonson, J. W., Oudah, M., Zonno, M., Gorovikov, S., Zhdanovich, S., Elfimov, I. S., Damascelli, A., Aronson, M. C.
In the past two decades, various classes of topological materials have been discovered, spanning topological insulators, semimetals, and metals. While the observation and understanding of the topology of a material has been a primary focus so far, th
Externí odkaz:
http://arxiv.org/abs/2407.08798
We describe DeepMachining, a deep learning-based AI system for online prediction of machining errors of lathe machine operations. We have built and evaluated DeepMachining based on manufacturing data from factories. Specifically, we first pretrain a
Externí odkaz:
http://arxiv.org/abs/2403.16451
Autor:
Yeh, Chun-Hsiao, Cheng, Ta-Ying, Hsieh, He-Yen, Lin, Chuan-En, Ma, Yi, Markham, Andrew, Trigoni, Niki, Kung, H. T., Chen, Yubei
Recent text-to-image diffusion models are able to learn and synthesize images containing novel, personalized concepts (e.g., their own pets or specific items) with just a few examples for training. This paper tackles two interconnected issues within
Externí odkaz:
http://arxiv.org/abs/2402.15504
Autor:
Lee, A. C., Sarkar, S., Du, K., Kung, H. -H., Won, C. J., Wang, K., Cheong, S. -W., Maiti, S., Blumberg, G.
Publikováno v:
Phys. Rev. B 109, L041111 (2024)
We use polarization resolved Raman spectroscopy to demonstrate that for a 3D giant Rashba system the bulk plasmon collective mode can directly couple to the Raman response even in the long wavelength $\mathbf q \rightarrow 0$ limit. Although conventi
Externí odkaz:
http://arxiv.org/abs/2310.04394
We propose Rosko -- row skipping outer products -- for deriving sparse matrix multiplication (SpMM) kernels in reducing computation and memory access requirements of deep neural networks (DNNs). Rosko allows skipping of entire row computations during
Externí odkaz:
http://arxiv.org/abs/2307.03930
We study surface states in the three-dimensional topological insulators Bi$_2$Te$_{3-x}$Se$_{x}$ (x = 0, 2, 3) by polarization resolved resonant Raman spectroscopy. By tracking the spectral intensity of the surface phonon modes with respect to the in
Externí odkaz:
http://arxiv.org/abs/2305.17546
We present the MEMA framework for the easy and quick derivation of efficient inference runtimes that minimize external memory accesses for matrix multiplication on TinyML systems. The framework accounts for hardware resource constraints and problem s
Externí odkaz:
http://arxiv.org/abs/2304.05544