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Artificial Neural Networks and Machine Learning – ICANN 2024 33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17–20, 2024, Proceedings, Part IV /

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 proceedin...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Wand, Michael (Editor), Malinovská, Kristína (Editor), Schmidhuber, Jürgen (Editor), Tetko, Igor V. (Editor)
Format: Electronic eBook
Language:English
Published: Cham : Springer Nature Switzerland : Imprint: Springer, 2024.
Edition:1st ed. 2024.
Series:Lecture Notes in Computer Science, 15019
Subjects:
Artificial intelligence.
Computers.
Application software.
Computer networks .
Artificial Intelligence.
Computing Milieux.
Computer and Information Systems Applications.
Computer Communication Networks.
Online Access:https://doi.org/10.1007/978-3-031-72341-4
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Table of Contents:
  • -- Brain-inspired ComputingBrain-inspired Computing.
  • A Multiscale Resonant Spiking Neural Network for Music Classification.
  • Masked Image Modeling as a Framework for Self-Supervised Learning across Eye Movements.
  • Serial Order Codes for Dimensionality Reduction in the Learning of Higher-Order Rules and Compositionality in Planning.
  • Sparsity aware Learning in Feedback-driven Differential Recurrent Neural Networks.
  • Towards Scalable GPU-Accelerated SNN Training via Temporal Fusion.
  • Cognitive and Computational Neuroscience.
  • Analysis of a Generative Model of Episodic Memory Based on Hierarchical VQ-VAE and Transformer.
  • Biologically-plausible Markov Chain Monte Carlo Sampling from Vector Symbolic Algebra-encoded Distributions.
  • Dynamic Graph for Biological Memory Modeling: A System-Level Validation.
  • EEG features learned by convolutional neural networks reflect alterations of social stimuli processing in autism.
  • Estimate of the Storage Capacity of q-Correlated Patterns in Hopfield Neural Networks.
  • An Accuracy-Shaping Mechanism for Competitive Distributed Learning.
  • Explainable Artificial Intelligence.
  • Counterfactual Contrastive Learning for Fine Grained Image Classification.
  • Enhancing Counterfactual Image Generation Using Mahalanobis Distance with Distribution Preferences in Feature Space.
  • Exploring Task-Specific Dimensions in Word Embeddings Through Automatic Rule Learning.
  • Generally-Occurring Model Change for Robust Counterfactual Explanations.
  • Model Based Clustering of Time Series Utilizing Expert ODEs.
  • Towards Generalizable and Interpretable AI-Modified Image Detectors.
  • Understanding Deep Networks via Multiscale Perturbations.
  • Robotics.
  • Details Make a Difference: Object State-Sensitive Neurorobotic Task Planning.
  • Neural Formation A*: A Knowledge-Data Hybrid-Driven Path Planning Algorithm for Multi-agent Formation Cooperation.
  • Robust Navigation for Unmanned Surface Vehicle Utilizing Improved Distributional Soft Actor-Critic.
  • When Robots Get Chatty: Grounding Multimodal Human-Robot Conversation and Collaboration.
  • Reinforcement Learning.
  • Asymmetric Actor-Critic for Adapting to Changing Environments in Reinforcement Learning.
  • Building surrogate models using trajectories of agents trained by Reinforcement Learning.
  • Demand-Responsive Transport Dynamic Scheduling Optimization Based on Multi-Agent Reinforcement Learning under Mixed Demand.
  • Dual Action Policy for Robust Sim-to-Real Reinforcement Learning.
  • Enhancing Visual Generalization in Reinforcement Learning with Cycling Augmentation.
  • Speeding up Meta-Exploration via Latent Representation.

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