Results 1 to 10 of about 1,067,034 (238)
Transfer learning for photonic delay-based reservoir computing to compensate parameter drift [PDF]
Nanophotonics, 2022 Photonic reservoir computing has been demonstrated to be able to solve various complex problems. Although training a reservoir computing system is much simpler compared to other neural network approaches, it still requires considerable amounts of ...
Bauwens Ian +4 more
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Towards Compute-Optimal Transfer Learning [PDF]
, 2023 The field of transfer learning is undergoing a significant shift with the introduction of large pretrained models which have demonstrated strong adaptability to a variety of downstream tasks. However, the high computational and memory requirements to finetune or use these models can be a hindrance to their widespread use.
Caccia, Massimo +8 more
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Computing masses from effective transfer matrices [PDF]
Physical Review D, 1994 (revised version: a few references added) LaTeX file, 25 pages, 6 PostScript figures, (revised version: a few references added)
Hasenbusch, M. +2 more
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Fast infrared radiative transfer calculations using graphics processing units: JURASSIC-GPU v2.0 [PDF]
Geoscientific Model Development, 2022 Remote sensing observations in the mid-infrared spectral region (4–15 µm) play a key role in monitoring the composition of the Earth's atmosphere. Mid-infrared spectral measurements from satellite, aircraft, balloons, and ground-based instruments provide
P. F. Baumeister, L. Hoffmann
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Frontiers in Virtual Reality, 2022 Virtual reality (VR) has seen increased use for training and instruction. Designers can enable VR users to gain insights into their own performance by visualizing telemetry data from their actions in VR. Our ability to detect patterns and trends visually
Andreas Bueckle +3 more
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Chemical Engineering Transactions, 2022 Many engineering problems involve heat transfer with phase change and their solution often lead to challenging heat transfer problems having no direct solution.
Lubomír Klimeš +4 more
doaj +1 more source
Virtual Machine Migration Strategy Based on Multi-Agent Deep Reinforcement Learning
Applied Sciences, 2021 Mobile edge computing is a new computing model, which pushes cloud computing power from centralized cloud to network edge. However, with the sinking of computing power, user mobility brings new challenges: since it is usually unstable, services should be
Yu Dai, Qiuhong Zhang, Lei Yang
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Nature Communications, 2022 Designing in-sensor computing systems remains a challenge. Here, the authors demonstrate artificial optical neurons based on the in-sensor computing architecture that fuses sensory and computing nodes into a single platform capable of reducing data ...
Doeon Lee +5 more
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Will computing in memory become a new dawn of associative processors?
Memories - Materials, Devices, Circuits and Systems, 2023 Computer architecture faces an enormous challenge in recent years: while the demand for performance is constantly growing, the performance improvement of general-purpose CPU has almost stalled.
Leonid Yavits
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FAST: Flexible and Low-Latency State Transfer in Mobile Edge Computing
IEEE Access, 2021 Mobile Edge Computing (MEC) brings the benefits of cloud computing, such as computation, networking, and storage resources, close to end users, thus reducing end-to-end latency and enabling various novel use cases, such as vehicle platooning, autonomous ...
Tung V. Doan +3 more
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