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Artificial Neural Networks and Machine Learning – ICANN 2024 (Record no. 63478)

MARC details
000 -LEADER
fixed length control field 07660nam a22006135i 4500
001 - CONTROL NUMBER
control field 978-3-031-72359-9
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20251030113049.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr nn 008mamaa
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 240917s2024 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783031723599
-- 978-3-031-72359-9
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-3-031-72359-9
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number Q334-342
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number TA347.A78
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYQ
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM004000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYQ
Source thema
245 10 - TITLE STATEMENT
Title Artificial Neural Networks and Machine Learning – ICANN 2024
Medium [electronic resource] :
Remainder of title 33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17–20, 2024, Proceedings, Part X /
Statement of responsibility, etc. edited by Michael Wand, Kristína Malinovská, Jürgen Schmidhuber, Igor V. Tetko.
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2024.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Cham :
Name of producer, publisher, distributor, manufacturer Springer Nature Switzerland :
-- Imprint: Springer,
Date of production, publication, distribution, manufacture, or copyright notice 2024.
300 ## - PHYSICAL DESCRIPTION
Extent XL, 438 p. 177 illus., 165 illus. in color.
Other physical details online resource.
336 ## - CONTENT TYPE
Content type term text
Content type code txt
Source rdacontent
337 ## - MEDIA TYPE
Media type term computer
Media type code c
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term online resource
Carrier type code cr
Source rdacarrier
347 ## - DIGITAL FILE CHARACTERISTICS
File type text file
Encoding format PDF
Source rda
490 1# - SERIES STATEMENT
Series statement Lecture Notes in Computer Science,
International Standard Serial Number 1611-3349 ;
Volume/sequential designation 15025
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note -- Workshop: AI in Drug Discovery. -- Combinatorial Library Neural Network (CoLiNN) for Combinatorial Library Visualization without Compound Enumeration. -- De novo Drug Design – Do We Really Want To Be “Original”? -- Elucidation of Molecular Substructures from Nuclear Magnetic Resonance Spectra using Gradient Boosting. -- Neural SHAKE: Geometric Constraints in Graph Generative Models. -- Scaffold Splits Overestimate Virtual Screening Performance. -- Target-Aware Drug Activity Model: A deep learning approach to virtual HTS. -- Workshop: Reservoir Computing. -- Effects of Input Structure and Topology on Input-Driven Functional Connectivity Stability. -- Non-dissipative Reservoir Computing approaches for time-series classification. -- Onion Echo State Networks A Preliminary Analysis of Dynamics. -- Oscillation-driven Reservoir Computing for Long-Term Replication of Chaotic Time Series. -- Prediction of reaching movements with target information towards trans-humeral prosthesis control using Reservoir Computing and LSTMs. -- Reducing Reservoir Dimensionality with Phase Space Construction for Simplified Hardware Implementation. -- Restricted Reservoirs on Heterogeneous Timescales. -- Special Session: Accuracy, Stability, and Robustness in Deep Neural Networks. -- Clean-image Backdoor Attacks. -- MADE: A Universal Fine-tuning Framework to Enhance Robustness of Machine Reading Comprehension. -- Robustness of biologically grounded neural networks against image perturbations. -- Some Comparisons of Linear and Deep ReLU Network Approximation. -- Unlearnable Examples Detection via Iterative Filtering. -- Special Session: Neurorobotics. -- Action recognition system integrating motion and object detection. -- Active Vision for Physical Robots using the Free Energy Principle. -- Learning Low-Level Causal Relations using a Simulated Robotic Arm. -- Modular Reinforcement Learning In Long-Horizon Manipulation Tasks. -- Robotic Model of the Mirror Neuron System: a Revival. -- Self-organized attractoring in locomoting animals and robots: an emerging field. -- Special Session: Spiking Neural Networks. -- A Multi-modal Spiking Meta-learner With Brain-inspired Task-aware Modulation Scheme. -- Event-Based Hand Detection on Neuromorphic Hardware Using a Sigma Delta Neural Network. -- Learning in Recurrent Spiking Neural Networks with Sparse full-FORCE Training. -- Natively neuromorphic LMU architecture for encoding-free SNN-based HAR on commercial edge devices. -- Obtaining Optimal Spiking Neural Network in Sequence Learning via CRNN-SNN Conversion. -- On Reducing Activity with Distillation and Regularization for Energy Ecient Spiking Neural Networks. -- Temporal Contrastive Learning for Spiking Neural Networks.
520 ## - SUMMARY, ETC.
Summary, etc. The ten-volume set LNCS 15016-15025 constitutes the refereed proceedings of the 33rd International Conference on Artificial Neural Networks and Machine Learning, ICANN 2024, held in Lugano, Switzerland, during September 17–20, 2024. The 294 full papers and 16 short papers included in these proceedings were carefully reviewed and selected from 764 submissions. The papers cover the following topics: Part I - theory of neural networks and machine learning; novel methods in machine learning; novel neural architectures; neural architecture search; self-organization; neural processes; novel architectures for computer vision; and fairness in machine learning. Part II - computer vision: classification; computer vision: object detection; computer vision: security and adversarial attacks; computer vision: image enhancement; and computer vision: 3D methods. Part III - computer vision: anomaly detection; computer vision: segmentation; computer vision: pose estimation and tracking; computer vision: video processing; computer vision: generative methods; and topics in computer vision. Part IV - brain-inspired computing; cognitive and computational neuroscience; explainable artificial intelligence; robotics; and reinforcement learning. Part V - graph neural networks; and large language models. Part VI - multimodality; federated learning; and time series processing. Part VII - speech processing; natural language processing; and language modeling. Part VIII - biosignal processing in medicine and physiology; and medical image processing. Part IX - human-computer interfaces; recommender systems; environment and climate; city planning; machine learning in engineering and industry; applications in finance; artificial intelligence in education; social network analysis; artificial intelligence and music; and software security. Part X - workshop: AI in drug discovery; workshop: reservoir computing; special session: accuracy, stability, and robustness in deep neural networks; special session: neurorobotics; and special session: spiking neural networks.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element
9 (RLIN) 58441
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element
9 (RLIN) 65793
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element
9 (RLIN) 60157
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element
9 (RLIN) 58441
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element
9 (RLIN) 66530
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element
9 (RLIN) 65689
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Wand, Michael.
Relator term editor.
Authority record control number (orcid)0000-0003-0966-7824
-- https://orcid.org/0000-0003-0966-7824
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Malinovská, Kristína.
Relator term editor.
Authority record control number (orcid)0000-0001-7638-028X
-- https://orcid.org/0000-0001-7638-028X
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Schmidhuber, Jürgen.
Relator term editor.
Authority record control number (orcid)0000-0002-1468-6758
-- https://orcid.org/0000-0002-1468-6758
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Tetko, Igor V.
Relator term editor.
Authority record control number (orcid)0000-0002-6855-0012
-- https://orcid.org/0000-0002-6855-0012
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer Nature eBook
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9783031723582
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9783031723605
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Lecture Notes in Computer Science,
International Standard Serial Number 1611-3349 ;
Volume number/sequential designation 15025
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/978-3-031-72359-9">https://doi.org/10.1007/978-3-031-72359-9</a>
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