Artificial Neural Networks and Machine Learning – ICANN 2024

33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17–20, 2024, Proceedings, Part X

Häftad, Engelska, 2024

Av Michael Wand, Kristína Malinovská, Jürgen Schmidhuber, Igor V. Tetko, Kristina Malinovska, Jurgen Schmidhuber

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and fairness in machine learning.Part II - computer vision: classification; and computer vision: 3D methods. Part III - computer vision: anomaly detection; and topics in computer vision. Part IV - brain-inspired computing;

Produktinformation

Utgivningsdatum2024-09-18
Mått155 x 235 x 26 mm
Vikt721 g
FormatHäftad
SpråkEngelska
SerieLecture Notes in Computer Science
Antal sidor438
FörlagSpringer International Publishing AG
ISBN9783031723582

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Tillämpad datateknik inom Data och it
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Informationsteknik: allmänt inom Data och it
Artificiell intelligens inom Data och it

.- 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 HardwareImplementation..- 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 SpikingNeural Networks..- Temporal Contrastive Learning for Spiking NeuralNetworks.