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Multiagent Reinforcement Learning-Based Adaptive Sampling for Conformational Dynamics of Proteins.
Journal of Chemical Theory and Computation, 2022Machine learning is increasingly applied to improve the efficiency and accuracy of molecular dynamics (MD) simulations. Although the growth of distributed computer clusters has allowed researchers to obtain higher amounts of data, unbiased MD simulations
D. Kleiman, D. Shukla
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IEEE Transactions on Geoscience and Remote Sensing, 2022
Graph convolutional networks (GCNs) have been shown to be effective for hyperspectral image (HSI) classification due to their capacity to learn representations of spatial–spectral features.
Yun Ding +4 more
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Graph convolutional networks (GCNs) have been shown to be effective for hyperspectral image (HSI) classification due to their capacity to learn representations of spatial–spectral features.
Yun Ding +4 more
semanticscholar +1 more source
UASNet: Uncertainty Adaptive Sampling Network for Deep Stereo Matching
IEEE International Conference on Computer Vision, 2021Recent studies have shown that cascade cost volume can play a vital role in deep stereo matching to achieve high resolution depth map with efficient hardware usage.
Yamin Mao +6 more
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Self-Adaptive Sampling for Network Traffic Measurement
IEEE Conference on Computer Communications, 2021Per-flow traffic measurement in the high-speed network plays an important role in many practical applications. Due to the limited on-chip memory and the mismatch between off-chip memory speed and line rate, sampling-based methods select and forward a ...
Yang Du +4 more
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Inverse Adaptive Cluster Sampling
Biometrics, 2001Consider a population in which the variable of interest tends to be at or near zero for many of the population units but a subgroup exhibits values distinctly different from zero. Such a population can be described as rare in the sense that the proportion of elements having nonzero values is very small.
Christman, Mary C., Lan, Feng
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On adaptive sampling algorithms for IoT devices
ICC 2021 - IEEE International Conference on Communications, 2021Sampling is a core process in IoT systems. It deter-mines the data volume circulating within the network as well as the energy consumption on the IoT devices.
Yassine Ben-Aboud +3 more
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Neural Temporal Adaptive Sampling and Denoising
Computer graphics forum (Print), 2020Despite recent advances in Monte Carlo path tracing at interactive rates, denoised image sequences generated with few samples per‐pixel often yield temporally unstable results and loss of high‐frequency details.
J. Hasselgren +4 more
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Adaptive sampling with an autonomous underwater vehicle in static marine environments
J. Field Robotics, 2020This paper explores the use of autonomous underwater vehicles (AUVs) equipped with sensors to construct water quality models to aid in the assessment of important environmental hazards, for instance related to point‐source pollutants or localized hypoxic
Paul G. Stankiewicz +2 more
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