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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.
List of contents
.- Epilepsy Prediction based on Intra- and Inter-Channel Feature Mixing.
.- Fine-grained Recognition of Arteriovenous Fistula Stenosis Using Blood Flow Sounds: An Animal Model-Based Dataset and a Frequency-Aware Decoupling Network.
.- SMART-RetroNet: A Framework for Chemical Retrosynthesis Prediction.
.- Few-shot Learning for Syndrome Differentiation with Two Prompts.
.- Neural QSLIM for Mesh Autoencoders.
.- Evolving Spatially Embedded Recurrent Spiking Neural Networks for Control Tasks.
.- Amortizing Personnalization in Virtual Brain Twins.
.- MPCCP:A Multi-chain Perception Crime Charge Prediction Method.
.- Beran Estimator Kernel Learning using Nearest-Neighbours and its Application to Reliability Analysis.
.- Conformalized Causal Learning for Uncertainty-Aware MineralProspectivity Mapping.
.- PhysMamba: Synergistic State Space Duality Model for Remote Physiological Measurement.
.- Proactive Depot Discovery: A Generative DRL Framework for Adaptive Location-Routing.
.- Learning Joint General and Specific Representation with Masked Auto-encoder for Radiology Report Generation.
.- Process Adaptive Learning for Visual-Language Navigation.
.- Audio-Driven Talking Head Generation with Emotion Based on FLAME Geometry Model.
.- Studying the Generalization Behavior of Surrogate Models for Punch-Bending by Generating Plausible Counterfactuals.
.- NGAT: A Node-level Graph Attention Network for Long-term Stock Prediction.
.- CSM: Corn Instance Segmentation Model Fusing Dilated Residual Networks and Low-Rank Adaptation.
.- Sensor-Enhanced PINNs for Contaminant Dispersion Modeling.
.- Uniform Representation of Parametric CAD Models for Generative Application.
.- Surrogate-Assisted Multi-Objective Design of Complex Multibody Systems.
.- KANLoc: WiFi Localization with A Lightweight KAN.
.- DualGF: Example-based Path Planning via Dual Gradient Fields.
.- Improving physics-informed neural network extrapolation via transfer learning and adaptive activation functions.
.- A Spiking Central Pattern Generator Capable of Adaptive Gait Control in Quadruped Locomotion.
.- ViSMoE: Visual-Aware Sparse Mixture-of-Experts for Embodied Referring Expression Grounding.
.- FDFRL: Credit Card Fraud Detection Based on Federated Reinforcement Learning.
.- MENGLAN:Multiscale Enhanced Nonparametric Gas Analyzer with Lightweight Architecture and Networks.
.- Targeted trust-based merging of customers opinions.
.- DA-NeRF: High-Fidelity Talking Face Generation From Speech With Neural Radiance Fields.
.- Beyond Reconstruction: A Physics Based Neural Deferred Shader for Photo-realistic Rendering.
.- Accurate SDF Reconstruction with Geometric-Differential Regularization and Categorized Sampling Strategy.
.- Optimized Supervised Control of Stochastic Timed Discrete Event Systems using Supervisory Control Theory and Reinforcement learning.
.- A Classification Algorithm for Bronchiolitis Obliterans in Pediatric CT Images with Extreme Class Imbalance.
.- DISEncoder:A Dual-Branch Query Encoder Using Graph Models for Distributed Databases.
.- A Subject-Independent Stress Detection Model Based on Temporal Feature Disentanglement.
Summary
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.
