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| Link zu diesem Datensatz | https://d-nb.info/1342300629 |
| Art des Inhalts | Konferenzschrift |
| Titel | Artificial Neural Networks and Machine Learning – ICANN 2024 : 33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17–20, 2024, Proceedings, Part X / edited by Michael Wand, Kristína Malinovská, Jürgen Schmidhuber, Igor V. Tetko |
| Person(en) |
Wand, Michael (Herausgeber) Malinovská, Kristína (Herausgeber) Schmidhuber, Jürgen (Herausgeber) Tetko, Igor (Herausgeber) |
| Organisation(en) | SpringerLink (Online service) (Sonstige) |
| Ausgabe | 1st ed. 2024 |
| Verlag | Cham : Springer Nature Switzerland, Imprint: Springer |
| Zeitliche Einordnung | Erscheinungsdatum: 2024 |
| Umfang/Format | Online-Ressource, XL, 438 p. 177 illus., 165 illus. in color. : online resource. |
| Andere Ausgabe(n) |
Printed edition:: ISBN: 978-3-031-72358-2 Printed edition:: ISBN: 978-3-031-72360-5 |
| Inhalt | -- 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 |
| Persistent Identifier |
URN: urn:nbn:de:101:1-2409180429358.554826939397 DOI: 10.1007/978-3-031-72359-9 |
| URL | https://doi.org/10.1007/978-3-031-72359-9 |
| ISBN/Einband/Preis | 978-3-031-72359-9 |
| Sprache(n) | Englisch (eng) |
| Beziehungen | Lecture Notes in Computer Science ; 15025 |
| DDC-Notation | 004.3 (maschinell ermittelte DDC-Kurznotation) |
| Sachgruppe(n) | 004 Informatik |
| Online-Zugriff | Archivobjekt öffnen |
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