Probabilistic Parametric Curves for Sequence Modeling PDF Download
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Author: Hug, Ronny
Publisher: KIT Scientific Publishing
ISBN: 3731511983
Category : Mathematics
Languages : en
Pages : 224
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Book Description
This work proposes a probabilistic extension to Bézier curves as a basis for effectively modeling stochastic processes with a bounded index set. The proposed stochastic process model is based on Mixture Density Networks and Bézier curves with Gaussian random variables as control points. A key advantage of this model is given by the ability to generate multi-mode predictions in a single inference step, thus avoiding the need for Monte Carlo simulation.
Author: Hug, Ronny
Publisher: KIT Scientific Publishing
ISBN: 3731511983
Category : Mathematics
Languages : en
Pages : 224
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Book Description
This work proposes a probabilistic extension to Bézier curves as a basis for effectively modeling stochastic processes with a bounded index set. The proposed stochastic process model is based on Mixture Density Networks and Bézier curves with Gaussian random variables as control points. A key advantage of this model is given by the ability to generate multi-mode predictions in a single inference step, thus avoiding the need for Monte Carlo simulation.
Author: Péter Galambos
Publisher: Springer Nature
ISBN: 3031196503
Category : Computers
Languages : en
Pages : 241
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Book Description
This volume constitutes the papers of two workshops which were held in conjunctionwith the First International Conference on Robotics, Computer Vision and Intelligent Systems,ROBOVIS 2020, Virtual Event, in November 4-6, 2020 and Second International Conference on Robotics, Computer Vision and Intelligent Systems,ROBOVIS 2021, Virtual Event, in October 25-27, 2021. The 11 revised full papers presented in this book were carefully reviewed and selectedfrom 53 submissions.
Author: Dürr, Fabian
Publisher: KIT Scientific Publishing
ISBN: 3731513145
Category :
Languages : en
Pages : 248
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Book Description
The understanding and interpretation of complex 3D environments is a key challenge of autonomous driving. Lidar sensors and their recorded point clouds are particularly interesting for this challenge since they provide accurate 3D information about the environment. This work presents a multimodal approach based on deep learning for panoptic segmentation of 3D point clouds. It builds upon and combines the three key aspects multi view architecture, temporal feature fusion, and deep sensor fusion.
Author: Beyerer, Jürgen
Publisher: KIT Scientific Publishing
ISBN: 3731513048
Category :
Languages : en
Pages : 140
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Book Description
In August 2022, Fraunhofer IOSB and IES of KIT held a joint workshop in a Schwarzwaldhaus near Triberg. Doctoral students presented research reports and discussed various topics like computer vision, optical metrology, network security, usage control, and machine learning. This book compiles the workshop's results and ideas, offering a comprehensive overview of the research program of IES and Fraunhofer IOSB.
Author: Meshram, Ankush
Publisher: KIT Scientific Publishing
ISBN: 3731512572
Category :
Languages : en
Pages : 224
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Book Description
Configuring an anomaly-based Network Intrusion Detection System for cybersecurity of an industrial system in the absence of information on networking infrastructure and programmed deterministic industrial process is challenging. Within the research work, different self-learning frameworks to analyze passively captured network traces from PROFINET-based industrial system for protocol-based and process behavior-based anomaly detection are developed, and evaluated on a real-world industrial system.
Author: Dirk Husmeier
Publisher: Springer Science & Business Media
ISBN: 9781852337780
Category : Computers
Languages : en
Pages : 540
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Book Description
Written for researchers and students in statistics, machine learning, and the biological sciences. This book provides a self-contained introduction to the methodology of Bayesian networks. It offers both elementary tutorials as well as more advanced applications and case studies.
Author: Philipp Hennig
Publisher: Cambridge University Press
ISBN: 1107163447
Category : Computers
Languages : en
Pages : 411
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Book Description
A thorough introduction to probabilistic numerics showing how to build more flexible, efficient, or customised algorithms for computation.
Author: Luis Enrique Sucar
Publisher: Springer
ISBN: 144716699X
Category : Computers
Languages : en
Pages : 253
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Book Description
This accessible text/reference provides a general introduction to probabilistic graphical models (PGMs) from an engineering perspective. The book covers the fundamentals for each of the main classes of PGMs, including representation, inference and learning principles, and reviews real-world applications for each type of model. These applications are drawn from a broad range of disciplines, highlighting the many uses of Bayesian classifiers, hidden Markov models, Bayesian networks, dynamic and temporal Bayesian networks, Markov random fields, influence diagrams, and Markov decision processes. Features: presents a unified framework encompassing all of the main classes of PGMs; describes the practical application of the different techniques; examines the latest developments in the field, covering multidimensional Bayesian classifiers, relational graphical models and causal models; provides exercises, suggestions for further reading, and ideas for research or programming projects at the end of each chapter.
Author: Somnath Datta
Publisher: Springer Nature
ISBN: 3030733513
Category : Medical
Languages : en
Pages : 349
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Book Description
Microbiome research has focused on microorganisms that live within the human body and their effects on health. During the last few years, the quantification of microbiome composition in different environments has been facilitated by the advent of high throughput sequencing technologies. The statistical challenges include computational difficulties due to the high volume of data; normalization and quantification of metabolic abundances, relative taxa and bacterial genes; high-dimensionality; multivariate analysis; the inherently compositional nature of the data; and the proper utilization of complementary phylogenetic information. This has resulted in an explosion of statistical approaches aimed at tackling the unique opportunities and challenges presented by microbiome data. This book provides a comprehensive overview of the state of the art in statistical and informatics technologies for microbiome research. In addition to reviewing demonstrably successful cutting-edge methods, particular emphasis is placed on examples in R that rely on available statistical packages for microbiome data. With its wide-ranging approach, the book benefits not only trained statisticians in academia and industry involved in microbiome research, but also other scientists working in microbiomics and in related fields.
Author: Aly Farag
Publisher: Springer Science & Business Media
ISBN: 0387683437
Category : Technology & Engineering
Languages : en
Pages : 581
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Book Description
This book covers the complete spectrum of deformable models, its evolution as an imagery field and its use in many biomedical engineering and clinical application disciplines. The book focuses on the core image processing techniques, theory and biomaterials useful to research and industry. Contributors are all pioneers in the field.
