Results 21 to 30 of about 1,868,423 (267)
IEEE Access, 2018 In this paper, a barrier Lyapunov function (BLF)-based backstepping control design is proposed for uncertain rigid spacecraft with both input and output constraints.
Zhongtian Chen +3 more
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A data-driven reflectance model [PDF]
ACM SIGGRAPH 2003 Papers, 2003 We present a generative model for isotropic bidirectional reflectance distribution functions (BRDFs) based on acquired reflectance data. Instead of using analytical reflectance models, we represent each BRDF as a dense set of measurements. This allows us to interpolate and extrapolate in the space of acquired BRDFs to create new BRDFs.
Matusik, Wojciech +3 more
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Gaussian Process Surrogates for Modeling Uncertainties in a Use Case of Forging Superalloys
Applied Sciences, 2022 The avoidance of scrap and the adherence to tolerances is an important goal in manufacturing. This requires a good engineering understanding of the underlying process. To achieve this, real physical experiments can be conducted.
Johannes G. Hoffer +2 more
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ETNA - Electronic Transactions on Numerical Analysis, 2022 We present a framework enabling variational data assimilation for gradient flows in general metric spaces, based on the minimizing movement (or Jordan-Kinderlehrer-Otto) approximation scheme. After discussing stability properties in the most general case, we specialise to the space of probability measures endowed with the Wasserstein distance.
Pietschmann, Jan-Frederik +1 more
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Self-supervised optimization of random material microstructures in the small-data regime
npj Computational Materials, 2022 While the forward and backward modeling of the process-structure-property chain has received a lot of attention from the materials’ community, fewer efforts have taken into consideration uncertainties.
Maximilian Rixner +1 more
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Data vs. Physics: The Apparent Pareto Front of Physics-Informed Neural Networks
IEEE Access, 2023 Physics-informed neural networks (PINNs) have emerged as a promising deep learning method, capable of solving forward and inverse problems governed by differential equations.
Franz M. Rohrhofer +3 more
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Data-Driven Innovation: What Is It? [PDF]
IEEE Transactions on Engineering Management, 2021 The future of innovation processes is anticipated to be more data-driven and empowered by the ubiquitous digitalization, increasing data accessibility and rapid advances in machine learning, artificial intelligence, and computing technologies. While the data-driven innovation (DDI) paradigm is emerging, it has yet been formally defined and theorized ...
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Complexity, 2018 In this paper, an adaptive finite-time fault-tolerant control scheme is proposed for the attitude stabilization of rigid spacecrafts. A first-order command filter is presented at the second step of the backstepping design to approximate the derivative of
Zhongtian Chen +3 more
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Data-Driven Color Manifolds [PDF]
ACM Transactions on Graphics, 2015 Color selection is required in many computer graphics applications, but can be tedious, as 1D or 2D user interfaces are employed to navigate in a 3D color space. Until now the problem was considered a question of designing general color spaces with meaningful (e.g., perceptual) parameters. In this work, we show how color selection usability improves by
Nguyen, C. +2 more
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Children with sickle cell disease (SCD) face multiple acute and chronic medical complications that may impact their quality of life as reported by patients themselves. Health‐related social needs (HRSNs), such as food and housing insecurity, are common in people with SCD, but the association between HRSNs and patient‐reported ...
Sarah J. Marks +5 more
wiley +1 more source