Artificial Neural Networks and Machine Learning - ICANN 2024
Artificial Neural Networks and Machine Learning - ICANN 2024
33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17-20, 2024, Proceedings, Part IV
Wand, Michael; Tetko, Igor V.; Schmidhuber, Juergen; Malinovska, Kristina
Springer International Publishing AG
10/2024
428
Mole
9783031723407
Pré-lançamento - envio 15 a 20 dias após a sua edição
.- 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.
.- 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.