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Author: Andrew T.C. Sutton Publisher: Springer Nature ISBN: 3031435834 Category : Science Languages : en Pages : 174
Book Description
This thesis presents significant advances in the use of neural networks to study the properties of neutrinos. Machine learning tools like neural networks (NN) can be used to identify the particle types or determine their energies in detectors such as those used in the NOvA neutrino experiment, which studies changes in a beam of neutrinos as it propagates approximately 800 km through the earth. NOvA relies heavily on simulations of the physics processes and the detector response; these simulations work well, but do not match the real experiment perfectly. Thus, neural networks trained on simulated datasets must include systematic uncertainties that account for possible imperfections in the simulation. This thesis presents the first application in HEP of adversarial domain generalization to a regression neural network. Applying domain generalization to problems with large systematic variations will reduce the impact of uncertainties while avoiding the risk of falsely constraining the phase space. Reducing the impact of systematic uncertainties makes NOvA analysis more robust, and improves the significance of experimental results.
Author: Andrew T.C. Sutton Publisher: Springer Nature ISBN: 3031435834 Category : Science Languages : en Pages : 174
Book Description
This thesis presents significant advances in the use of neural networks to study the properties of neutrinos. Machine learning tools like neural networks (NN) can be used to identify the particle types or determine their energies in detectors such as those used in the NOvA neutrino experiment, which studies changes in a beam of neutrinos as it propagates approximately 800 km through the earth. NOvA relies heavily on simulations of the physics processes and the detector response; these simulations work well, but do not match the real experiment perfectly. Thus, neural networks trained on simulated datasets must include systematic uncertainties that account for possible imperfections in the simulation. This thesis presents the first application in HEP of adversarial domain generalization to a regression neural network. Applying domain generalization to problems with large systematic variations will reduce the impact of uncertainties while avoiding the risk of falsely constraining the phase space. Reducing the impact of systematic uncertainties makes NOvA analysis more robust, and improves the significance of experimental results.
Author: Virginio Cantoni Publisher: Springer Science & Business Media ISBN: 1489910042 Category : Science Languages : en Pages : 399
Book Description
The following are the proceedings of the Third International Workshop on Perception held in Pavia, Italy, on September 27-30, 1993, under the auspices of four institutions: the Group of Cybernetic and Biophysics (GNCB)s of the National Research Council (CNR), the Italian Association for Artificial Intelligence (AI * IA), the Italian Association of Psychology (AlP), and the Italian Chapter of the International Association for Pattern Recognition (IAPR). The theme of this third workshop was: "Human and Machine Vision: Analogies and Divergencies." A wide spectrum of topics was covered, ranging from neurophysiology, to computer architecture, to psychology, to image understanding, etc. For this reason the structure of this workshop was quite different from those of the first two held in Parma (1991), and Trieste (1992). This time the workshop was composed of just eight modules, each one consisting of two invited lectures (dealing with vision in nature and machines, respectively) and a common panel discussion (including the two lecturers and three invited panellists).
Author: Robert Garnett Publisher: Frontiers Media SA ISBN: 283253774X Category : Science Languages : en Pages : 113
Book Description
Artificial Intelligence (AI) and Machine learning (ML) promise significant enhancements for particle accelerator operations, including applications in diagnostics, controls, and modeling. Challenges still exist in experimentally verifying AI/ML methods before deployment at user facilities. The ability to quickly generalize and adapt these methods to new operating configurations at the same facility or between facilities also remains a challenge and requires combining model-independent adaptive feedback with traditional ML tools. These methods also apply to the detection, classification, and prevention of operational anomalies that can cause accelerator damage or excessive beam loss in the case of abnormal operations. Opportunity exists in broadening AI/ML methods for early detection of a broad range of accelerator component or subsystem failures.
Author: Massih-Reza Amini Publisher: Springer Nature ISBN: 3031264126 Category : Computers Languages : en Pages : 680
Book Description
The multi-volume set LNAI 13713 until 13718 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2022, which took place in Grenoble, France, in September 2022. The 236 full papers presented in these proceedings were carefully reviewed and selected from a total of 1060 submissions. In addition, the proceedings include 17 Demo Track contributions. The volumes are organized in topical sections as follows: Part I: Clustering and dimensionality reduction; anomaly detection; interpretability and explainability; ranking and recommender systems; transfer and multitask learning; Part II: Networks and graphs; knowledge graphs; social network analysis; graph neural networks; natural language processing and text mining; conversational systems; Part III: Deep learning; robust and adversarial machine learning; generative models; computer vision; meta-learning, neural architecture search; Part IV: Reinforcement learning; multi-agent reinforcement learning; bandits and online learning; active and semi-supervised learning; private and federated learning; Part V: Supervised learning; probabilistic inference; optimal transport; optimization; quantum, hardware; sustainability; Part VI: Time series; financial machine learning; applications; applications: transportation; demo track.
Author: Hujun Yin Publisher: Springer Nature ISBN: 3030336174 Category : Computers Languages : en Pages : 376
Book Description
This two-volume set of LNCS 11871 and 11872 constitutes the thoroughly refereed conference proceedings of the 20th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2019, held in Manchester, UK, in November 2019. The 94 full papers presented were carefully reviewed and selected from 149 submissions. These papers provided a timely sample of the latest advances in data engineering and machine learning, from methodologies, frameworks, and algorithms to applications. The core themes of IDEAL 2019 include big data challenges, machine learning, data mining, information retrieval and management, bio-/neuro-informatics, bio-inspired models (including neural networks, evolutionary computation and swarm intelligence), agents and hybrid intelligent systems, real-world applications of intelligent techniques and AI.
Author: Denilson Barbosa Publisher: Springer ISBN: 3319183567 Category : Computers Languages : en Pages : 361
Book Description
This book constitutes the refereed proceedings of the 28th Canadian Conference on Artificial Intelligence, Canadian AI 2015, held in Halifax, Nova Scotia, Canada, in June 2015.The 15 regular papers and 12 short papers presented together with 8 papers from the Graduate Student Symposium were carefully reviewed and selected from 81 submissions. The papers are organized in topical sections such as agents, uncertainty and games; AI applications; NLP, text and social media mining; data mining and machine learning.
Author: Publisher: ISBN: Category : Aeronautics Languages : en Pages : 892
Book Description
Lists citations with abstracts for aerospace related reports obtained from world wide sources and announces documents that have recently been entered into the NASA Scientific and Technical Information Database.
Author: Weihua Yang Publisher: Nova Publishers ISBN: 9781604561852 Category : Technology & Engineering Languages : en Pages : 374
Book Description
Autonomous robots are robots which can perform desired tasks in unstructured environments without continuous human guidance. Many kinds of robots have some degree of autonomy. Different robots can be autonomous in different ways. A high degree of autonomy is particularly desirable in fields such as space exploration, where communication delays and interruptions are unavoidable. Some modern factory robots are "autonomous" within the strict confines of their direct environment. The exact orientation and position of the next object of work and (in the more advanced factories) even the type of object and the required task must be determined. This can vary unpredictably (at least from the robot's point of view). One important area of robotics research is to enable the robot to cope with its environment whether this be on land, underwater, in the air, underground, or in space. This book presents the latest research from around the globe.
Author: Ana Madevska Bogdanova Publisher: Springer ISBN: 3319098799 Category : Technology & Engineering Languages : en Pages : 362
Book Description
Data is a common ground, a starting point for each ICT system. Data needs processing, use of different technologies and state-of-the-art methods in order to obtain new knowledge, to develop new useful applications that not only ease, but also increase the quality of life. These applications use the exploration of Big Data, High throughput data, Data Warehouse, Data Mining, Bioinformatics, Robotics, with data coming from social media, sensors, scientific applications, surveillance, video and image archives, internet texts and documents, internet search indexing, medical records, business transactions, web logs, etc. Information and communication technologies have become the asset in everyday life enabling increased level of communication, processing and information exchange. This book offers a collection of selected papers presented at the Sixth International Conference on ICT Innovations held in September 2014, in Ohrid, Macedonia, with main topic World of data. The conference gathered academics, professionals and practitioners in developing solutions and systems in the industrial and business arena, especially innovative commercial implementations, novel applications of technology, and experience in applying recent ICT research advances to practical solutions.
Author: Andrew T.C. Sutton
Author: Andrew T.C. Sutton
Author: Virginio Cantoni
Author: Robert Garnett
Author: Massih-Reza Amini
Author: Hujun Yin
Author: Denilson Barbosa
Author: 
Author: Weihua Yang
Author: Jonathan Matthew Gratch
Author: Ana Madevska Bogdanova