Results 21 to 30 of about 9,437,008 (290)
A set-based approach to dynamic system design using physics informed neural network
Journal of Advanced Mechanical Design, Systems, and Manufacturing, 2022 In the early stage of dynamic system development which has a multi-disciplinary and hierarchical structure, system requirements need to be cascaded down to target values of each component so that engineers can collaborate efficiently and concurrently ...
Kohei SHINTANI +2 more
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Noisy Bayesian active learning [PDF]
2012 50th Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2012 39 pages (one-column), 5 figures, submitted to IEEE Transactions on Information ...
Mohammad Naghshvar +2 more
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A Bayesian framework for active learning [PDF]
The 2010 International Joint Conference on Neural Networks (IJCNN), 2010 We describe a Bayesian framework for active learning for non-separable data, which incorporates a query density to explicitly model how new data is to be sampled. The model makes no assumption of independence between queried data-points; rather it updates model parameters on the basis of both observations and how those observations were sampled.
Richard Fredlund +2 more
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Targeted Active Learning for Bayesian Decision-Making [PDF]
CoRR, 2021 Peer ...
Filstroff, Louis +5 more
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npj Computational Materials, 2023 Machine learning interatomic force fields are promising for combining high computational efficiency and accuracy in modeling quantum interactions and simulating atomistic dynamics.
Yu Xie +5 more
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Efficacy of Bayesian Neural Networks in Active Learning [PDF]
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2021 Published at CVPR Workshop on Learning From Limited or Imperfect Data (LLID ...
Vineeth Rakesh, Swayambhoo Jain
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Bayesian Pure-Tone Audiometry Through Active Learning Under Informed Priors
Frontiers in Digital Health, 2021 Pure-tone audiometry—the process of estimating a person's hearing threshold from “audible” and “inaudible” responses to tones of varying frequency and intensity—is the basis for diagnosing and quantifying hearing loss.
Marco Cox, Bert de Vries, Bert de Vries
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Active Bayesian perception and reinforcement learning [PDF]
2013 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2013 In a series of papers, we have formalized an active Bayesian perception approach for robotics based on recent progress in understanding animal perception. However, an issue for applied robot perception is how to tune this method to a task, using: (i) a belief threshold that adjusts the speed-accuracy tradeoff; and (ii) an active control strategy for ...
Nathan F. Lepora +3 more
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Prediction-Oriented Bayesian Active Learning
CoRR, 2023 Information-theoretic approaches to active learning have traditionally focused on maximising the information gathered about the model parameters, most commonly by optimising the BALD score. We highlight that this can be suboptimal from the perspective of predictive performance.
Freddie Bickford Smith +5 more
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Active Inference Integrated With Imitation Learning for Autonomous Driving
IEEE Access, 2022 Classical imitation learning methods suffer substantially from the learning hierarchical policies when the imitative agent faces an unobserved state by the expert agent.
Sheida Nozari +5 more
doaj +1 more source