Artificial Neural Networks and Machine Learning - ICANN 2025
34th International Conference on Artificial Neural Networks, Kaunas, Lithuania, September 9-12, 2025, Proceedings, Part I
Herausgeber: Senn, Walter; Bengio, Yoshua; Jirsa, Viktor; Villa, Alessandro E. P; Tetko, Igor V.; Saudargiene, Ausra; Sanguineti, Marcello
Artificial Neural Networks and Machine Learning - ICANN 2025
34th International Conference on Artificial Neural Networks, Kaunas, Lithuania, September 9-12, 2025, Proceedings, Part I
Herausgeber: Senn, Walter; Bengio, Yoshua; Jirsa, Viktor; Villa, Alessandro E. P; Tetko, Igor V.; Saudargiene, Ausra; Sanguineti, Marcello
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The four-volume set LNCS 16068-16071 constitutes the proceedings of the 34th International Conference on Artificial Neural Networks and Machine Learning, ICANN 2025, held in Kaunas, Lithuania, September 9–12, 2025. The 170 full papers and 8 abstracts included in these conference proceedings were carefully reviewed and selected from 375 submissions. The conference strongly values the synergy between theoretical progress and impactful real-world applications, and actively encourages contributions that demonstrate how artificial neural networks are being used to address pressing societal and technological challenges.…mehr
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The four-volume set LNCS 16068-16071 constitutes the proceedings of the 34th International Conference on Artificial Neural Networks and Machine Learning, ICANN 2025, held in Kaunas, Lithuania, September 9–12, 2025. The 170 full papers and 8 abstracts included in these conference proceedings were carefully reviewed and selected from 375 submissions. The conference strongly values the synergy between theoretical progress and impactful real-world applications, and actively encourages contributions that demonstrate how artificial neural networks are being used to address pressing societal and technological challenges.
Produktdetails
- Produktdetails
- Lecture Notes in Computer Science Nr.16068
- Verlag: Springer International Publishing AG / Springer-Verlag GmbH
- Artikelnr. des Verlages: 89554319
- Seitenzahl: 648
- Erscheinungstermin: 8. Oktober 2025
- Englisch
- Abmessung: 235mm x 155mm
- ISBN-13: 9783032045577
- ISBN-10: 3032045576
- Artikelnr.: 75021021
- Herstellerkennzeichnung
- Springer-Verlag GmbH
- Tiergartenstr. 17
- 69121 Heidelberg
- ProductSafety@springernature.com
- Lecture Notes in Computer Science Nr.16068
- Verlag: Springer International Publishing AG / Springer-Verlag GmbH
- Artikelnr. des Verlages: 89554319
- Seitenzahl: 648
- Erscheinungstermin: 8. Oktober 2025
- Englisch
- Abmessung: 235mm x 155mm
- ISBN-13: 9783032045577
- ISBN-10: 3032045576
- Artikelnr.: 75021021
- Herstellerkennzeichnung
- Springer-Verlag GmbH
- Tiergartenstr. 17
- 69121 Heidelberg
- ProductSafety@springernature.com
.
MRT
NAS: Boosting Training
free NAS via Manifold Regularization. .
MSfusion: A Dynamic Model Splitting Approach for Resource Constrained Machines to Collaboratively Train Larger Models. .
DeepCTL: Neural Branching
Time CTL Satisfiability Checking via Recursive Decision Trees. .
MFMamba: A Hierarchical Weakly Causal Mamba with Multi
Scale Feature Fusion for Vision Tasks. .
Characterizing trainability, expressivity and generalization of neural architecture with metrics from neural tangent kernel. .
Unrolled Neural Adaptive Alternating Gradient Descent for NMF. .
FedTP: Traceable Passport
based Ownership Verification for Federated Deep Neural Network Models. .
Learning to Optimize Entropy in the Soft Actor
Critic. .
Parallelizing Sharpness
Aware Minimization: A Semi
Asynchronous Small
Batch Approach. .
Small transformer architectures for task switching. .
Stochastic Covariance Regularization for Imbalanced Datasets. .
Efficient Learning in Spiking Neural Networks
Introducing Feedback Alignment to the Reinforced Liquid State Machine. .
Object
Centric Dreamer. .
How Inductive Biases Affect OOD Generalization: An Investigation in Formal Language Recognition with Autoregressive Models. .
Brain Generative Replay for Continual Learning. .
Dynamic Ensembles Towards Out
Of
Distribution Generalization of Affect Models. .
D2R: Dual Regularization Loss with Collaborative Adversarial Generation for Model Robustness. .
The Power of Max Pooling Layer. .
Firing rates and representational error in efficient spiking networks are bounded by design. .
CIBR: Cross
modal Information Bottleneck Regularization for Robust CLIP Generalization. .
Cascade Pre
Attention: Regulating Neuronal Activation Distributions in MetaFormer
Based Spiking Neural Networks. .
MTL
SIMNAS: Task Similarity
Driven Neural Architecture Search for Enhanced Multi
Task Learning. .
Towards Better Graph Anomaly Detection: A Performance
Aware Neural Architecture Search Approach. .
Improving Stability of Parameter Sharing in Cooperative Multi
Agent Reinforcement Learning. .
The Explainability
Performance Coefficient: A New Metric for Model Transparency. .
GLFMamba
U: Global
Local Fused Mamba
Unet. .
Continuous Fair SMOTE
Fairness
Aware Stream Learning from Imbalanced Data. .
Evaluating the Impact of Data Curation on Off
Policy Reinforcement Learning. .
Enhancing Graph Neural Networks with Mixup
Based Knowledge Distillation. .
A Framework for Uncertainty Quantification Based on Nearest Neighbors Across Layers. .
FedP2PAvg: A Peer
to
Peer Collaborative Framework for Federated Learning in Non
IID Scenarios. .
Correcting the Modified Stochastic Synaptic Model of Synaptic Dynamics
Refinement of Vesicle and Neurotransmitters Functions. .
Improving monotonic optimization in heterogeneous multi
agent reinforcement learning with optimal marginal deterministic policy gradient. .
Efficient ReliefF: A low
power optimization of ReliefF for resource
constrained devices. .
Enhancing Adversarial Robustness through Multi
Objective Representation Learning. .
Trustworthy Learning with Noisy Labels. .
Effect of Neuromodulation on the Brain Dynamical Repertoire. .
Classification of large data sets by neural networks: A probabilistic viewpoint. .
Identification and Realization of a Class of Discrete Event Systems by Neural Networks
Timed Petri Nets. .
Dopamine
modulated Learning and Decision
making with Neuromorphic Computing. .
A Unified Platform to Evaluate STDP Learning Rule and Synapse Model using Pattern Recognition in a Spiking Neural Network. .
XOOD: A Self
Supervised Algorithm for Detecting Out
of
Distribution Data for Image Classification. .
Perpetual Generation: Online Learning of Linear State
Space Models from a Single Stream. .
Accelerating Spatiotemporal Learning with minConvRNNs. .
Full Integer Arithmetic Online Training for Spiking Neural Networks. .
Regularised Loss Function for Goal Recognition as a Deep Learning Task. .
Improving Consistency Distillation with Rectified Trajectories. .
Merging versus Separating Replay Samples in Continual Learning. .
Signal
to
noise difference as a correlate of class learning in neural networks. .
Catastrophic Forgetting Mitigation via Discrepancy
Weighted Experience Replay. .
Supervised feature selection with class self
representation. .
Complexity and Criticality in Neuro
Inspired Reservoirs. .
A Fokker
Planck Perspective on the Flow of Information in Continuous Memory Neural Networks.
MRT
NAS: Boosting Training
free NAS via Manifold Regularization. .
MSfusion: A Dynamic Model Splitting Approach for Resource Constrained Machines to Collaboratively Train Larger Models. .
DeepCTL: Neural Branching
Time CTL Satisfiability Checking via Recursive Decision Trees. .
MFMamba: A Hierarchical Weakly Causal Mamba with Multi
Scale Feature Fusion for Vision Tasks. .
Characterizing trainability, expressivity and generalization of neural architecture with metrics from neural tangent kernel. .
Unrolled Neural Adaptive Alternating Gradient Descent for NMF. .
FedTP: Traceable Passport
based Ownership Verification for Federated Deep Neural Network Models. .
Learning to Optimize Entropy in the Soft Actor
Critic. .
Parallelizing Sharpness
Aware Minimization: A Semi
Asynchronous Small
Batch Approach. .
Small transformer architectures for task switching. .
Stochastic Covariance Regularization for Imbalanced Datasets. .
Efficient Learning in Spiking Neural Networks
Introducing Feedback Alignment to the Reinforced Liquid State Machine. .
Object
Centric Dreamer. .
How Inductive Biases Affect OOD Generalization: An Investigation in Formal Language Recognition with Autoregressive Models. .
Brain Generative Replay for Continual Learning. .
Dynamic Ensembles Towards Out
Of
Distribution Generalization of Affect Models. .
D2R: Dual Regularization Loss with Collaborative Adversarial Generation for Model Robustness. .
The Power of Max Pooling Layer. .
Firing rates and representational error in efficient spiking networks are bounded by design. .
CIBR: Cross
modal Information Bottleneck Regularization for Robust CLIP Generalization. .
Cascade Pre
Attention: Regulating Neuronal Activation Distributions in MetaFormer
Based Spiking Neural Networks. .
MTL
SIMNAS: Task Similarity
Driven Neural Architecture Search for Enhanced Multi
Task Learning. .
Towards Better Graph Anomaly Detection: A Performance
Aware Neural Architecture Search Approach. .
Improving Stability of Parameter Sharing in Cooperative Multi
Agent Reinforcement Learning. .
The Explainability
Performance Coefficient: A New Metric for Model Transparency. .
GLFMamba
U: Global
Local Fused Mamba
Unet. .
Continuous Fair SMOTE
Fairness
Aware Stream Learning from Imbalanced Data. .
Evaluating the Impact of Data Curation on Off
Policy Reinforcement Learning. .
Enhancing Graph Neural Networks with Mixup
Based Knowledge Distillation. .
A Framework for Uncertainty Quantification Based on Nearest Neighbors Across Layers. .
FedP2PAvg: A Peer
to
Peer Collaborative Framework for Federated Learning in Non
IID Scenarios. .
Correcting the Modified Stochastic Synaptic Model of Synaptic Dynamics
Refinement of Vesicle and Neurotransmitters Functions. .
Improving monotonic optimization in heterogeneous multi
agent reinforcement learning with optimal marginal deterministic policy gradient. .
Efficient ReliefF: A low
power optimization of ReliefF for resource
constrained devices. .
Enhancing Adversarial Robustness through Multi
Objective Representation Learning. .
Trustworthy Learning with Noisy Labels. .
Effect of Neuromodulation on the Brain Dynamical Repertoire. .
Classification of large data sets by neural networks: A probabilistic viewpoint. .
Identification and Realization of a Class of Discrete Event Systems by Neural Networks
Timed Petri Nets. .
Dopamine
modulated Learning and Decision
making with Neuromorphic Computing. .
A Unified Platform to Evaluate STDP Learning Rule and Synapse Model using Pattern Recognition in a Spiking Neural Network. .
XOOD: A Self
Supervised Algorithm for Detecting Out
of
Distribution Data for Image Classification. .
Perpetual Generation: Online Learning of Linear State
Space Models from a Single Stream. .
Accelerating Spatiotemporal Learning with minConvRNNs. .
Full Integer Arithmetic Online Training for Spiking Neural Networks. .
Regularised Loss Function for Goal Recognition as a Deep Learning Task. .
Improving Consistency Distillation with Rectified Trajectories. .
Merging versus Separating Replay Samples in Continual Learning. .
Signal
to
noise difference as a correlate of class learning in neural networks. .
Catastrophic Forgetting Mitigation via Discrepancy
Weighted Experience Replay. .
Supervised feature selection with class self
representation. .
Complexity and Criticality in Neuro
Inspired Reservoirs. .
A Fokker
Planck Perspective on the Flow of Information in Continuous Memory Neural Networks.
.
MRT
NAS: Boosting Training
free NAS via Manifold Regularization. .
MSfusion: A Dynamic Model Splitting Approach for Resource Constrained Machines to Collaboratively Train Larger Models. .
DeepCTL: Neural Branching
Time CTL Satisfiability Checking via Recursive Decision Trees. .
MFMamba: A Hierarchical Weakly Causal Mamba with Multi
Scale Feature Fusion for Vision Tasks. .
Characterizing trainability, expressivity and generalization of neural architecture with metrics from neural tangent kernel. .
Unrolled Neural Adaptive Alternating Gradient Descent for NMF. .
FedTP: Traceable Passport
based Ownership Verification for Federated Deep Neural Network Models. .
Learning to Optimize Entropy in the Soft Actor
Critic. .
Parallelizing Sharpness
Aware Minimization: A Semi
Asynchronous Small
Batch Approach. .
Small transformer architectures for task switching. .
Stochastic Covariance Regularization for Imbalanced Datasets. .
Efficient Learning in Spiking Neural Networks
Introducing Feedback Alignment to the Reinforced Liquid State Machine. .
Object
Centric Dreamer. .
How Inductive Biases Affect OOD Generalization: An Investigation in Formal Language Recognition with Autoregressive Models. .
Brain Generative Replay for Continual Learning. .
Dynamic Ensembles Towards Out
Of
Distribution Generalization of Affect Models. .
D2R: Dual Regularization Loss with Collaborative Adversarial Generation for Model Robustness. .
The Power of Max Pooling Layer. .
Firing rates and representational error in efficient spiking networks are bounded by design. .
CIBR: Cross
modal Information Bottleneck Regularization for Robust CLIP Generalization. .
Cascade Pre
Attention: Regulating Neuronal Activation Distributions in MetaFormer
Based Spiking Neural Networks. .
MTL
SIMNAS: Task Similarity
Driven Neural Architecture Search for Enhanced Multi
Task Learning. .
Towards Better Graph Anomaly Detection: A Performance
Aware Neural Architecture Search Approach. .
Improving Stability of Parameter Sharing in Cooperative Multi
Agent Reinforcement Learning. .
The Explainability
Performance Coefficient: A New Metric for Model Transparency. .
GLFMamba
U: Global
Local Fused Mamba
Unet. .
Continuous Fair SMOTE
Fairness
Aware Stream Learning from Imbalanced Data. .
Evaluating the Impact of Data Curation on Off
Policy Reinforcement Learning. .
Enhancing Graph Neural Networks with Mixup
Based Knowledge Distillation. .
A Framework for Uncertainty Quantification Based on Nearest Neighbors Across Layers. .
FedP2PAvg: A Peer
to
Peer Collaborative Framework for Federated Learning in Non
IID Scenarios. .
Correcting the Modified Stochastic Synaptic Model of Synaptic Dynamics
Refinement of Vesicle and Neurotransmitters Functions. .
Improving monotonic optimization in heterogeneous multi
agent reinforcement learning with optimal marginal deterministic policy gradient. .
Efficient ReliefF: A low
power optimization of ReliefF for resource
constrained devices. .
Enhancing Adversarial Robustness through Multi
Objective Representation Learning. .
Trustworthy Learning with Noisy Labels. .
Effect of Neuromodulation on the Brain Dynamical Repertoire. .
Classification of large data sets by neural networks: A probabilistic viewpoint. .
Identification and Realization of a Class of Discrete Event Systems by Neural Networks
Timed Petri Nets. .
Dopamine
modulated Learning and Decision
making with Neuromorphic Computing. .
A Unified Platform to Evaluate STDP Learning Rule and Synapse Model using Pattern Recognition in a Spiking Neural Network. .
XOOD: A Self
Supervised Algorithm for Detecting Out
of
Distribution Data for Image Classification. .
Perpetual Generation: Online Learning of Linear State
Space Models from a Single Stream. .
Accelerating Spatiotemporal Learning with minConvRNNs. .
Full Integer Arithmetic Online Training for Spiking Neural Networks. .
Regularised Loss Function for Goal Recognition as a Deep Learning Task. .
Improving Consistency Distillation with Rectified Trajectories. .
Merging versus Separating Replay Samples in Continual Learning. .
Signal
to
noise difference as a correlate of class learning in neural networks. .
Catastrophic Forgetting Mitigation via Discrepancy
Weighted Experience Replay. .
Supervised feature selection with class self
representation. .
Complexity and Criticality in Neuro
Inspired Reservoirs. .
A Fokker
Planck Perspective on the Flow of Information in Continuous Memory Neural Networks.
MRT
NAS: Boosting Training
free NAS via Manifold Regularization. .
MSfusion: A Dynamic Model Splitting Approach for Resource Constrained Machines to Collaboratively Train Larger Models. .
DeepCTL: Neural Branching
Time CTL Satisfiability Checking via Recursive Decision Trees. .
MFMamba: A Hierarchical Weakly Causal Mamba with Multi
Scale Feature Fusion for Vision Tasks. .
Characterizing trainability, expressivity and generalization of neural architecture with metrics from neural tangent kernel. .
Unrolled Neural Adaptive Alternating Gradient Descent for NMF. .
FedTP: Traceable Passport
based Ownership Verification for Federated Deep Neural Network Models. .
Learning to Optimize Entropy in the Soft Actor
Critic. .
Parallelizing Sharpness
Aware Minimization: A Semi
Asynchronous Small
Batch Approach. .
Small transformer architectures for task switching. .
Stochastic Covariance Regularization for Imbalanced Datasets. .
Efficient Learning in Spiking Neural Networks
Introducing Feedback Alignment to the Reinforced Liquid State Machine. .
Object
Centric Dreamer. .
How Inductive Biases Affect OOD Generalization: An Investigation in Formal Language Recognition with Autoregressive Models. .
Brain Generative Replay for Continual Learning. .
Dynamic Ensembles Towards Out
Of
Distribution Generalization of Affect Models. .
D2R: Dual Regularization Loss with Collaborative Adversarial Generation for Model Robustness. .
The Power of Max Pooling Layer. .
Firing rates and representational error in efficient spiking networks are bounded by design. .
CIBR: Cross
modal Information Bottleneck Regularization for Robust CLIP Generalization. .
Cascade Pre
Attention: Regulating Neuronal Activation Distributions in MetaFormer
Based Spiking Neural Networks. .
MTL
SIMNAS: Task Similarity
Driven Neural Architecture Search for Enhanced Multi
Task Learning. .
Towards Better Graph Anomaly Detection: A Performance
Aware Neural Architecture Search Approach. .
Improving Stability of Parameter Sharing in Cooperative Multi
Agent Reinforcement Learning. .
The Explainability
Performance Coefficient: A New Metric for Model Transparency. .
GLFMamba
U: Global
Local Fused Mamba
Unet. .
Continuous Fair SMOTE
Fairness
Aware Stream Learning from Imbalanced Data. .
Evaluating the Impact of Data Curation on Off
Policy Reinforcement Learning. .
Enhancing Graph Neural Networks with Mixup
Based Knowledge Distillation. .
A Framework for Uncertainty Quantification Based on Nearest Neighbors Across Layers. .
FedP2PAvg: A Peer
to
Peer Collaborative Framework for Federated Learning in Non
IID Scenarios. .
Correcting the Modified Stochastic Synaptic Model of Synaptic Dynamics
Refinement of Vesicle and Neurotransmitters Functions. .
Improving monotonic optimization in heterogeneous multi
agent reinforcement learning with optimal marginal deterministic policy gradient. .
Efficient ReliefF: A low
power optimization of ReliefF for resource
constrained devices. .
Enhancing Adversarial Robustness through Multi
Objective Representation Learning. .
Trustworthy Learning with Noisy Labels. .
Effect of Neuromodulation on the Brain Dynamical Repertoire. .
Classification of large data sets by neural networks: A probabilistic viewpoint. .
Identification and Realization of a Class of Discrete Event Systems by Neural Networks
Timed Petri Nets. .
Dopamine
modulated Learning and Decision
making with Neuromorphic Computing. .
A Unified Platform to Evaluate STDP Learning Rule and Synapse Model using Pattern Recognition in a Spiking Neural Network. .
XOOD: A Self
Supervised Algorithm for Detecting Out
of
Distribution Data for Image Classification. .
Perpetual Generation: Online Learning of Linear State
Space Models from a Single Stream. .
Accelerating Spatiotemporal Learning with minConvRNNs. .
Full Integer Arithmetic Online Training for Spiking Neural Networks. .
Regularised Loss Function for Goal Recognition as a Deep Learning Task. .
Improving Consistency Distillation with Rectified Trajectories. .
Merging versus Separating Replay Samples in Continual Learning. .
Signal
to
noise difference as a correlate of class learning in neural networks. .
Catastrophic Forgetting Mitigation via Discrepancy
Weighted Experience Replay. .
Supervised feature selection with class self
representation. .
Complexity and Criticality in Neuro
Inspired Reservoirs. .
A Fokker
Planck Perspective on the Flow of Information in Continuous Memory Neural Networks.