Artificial Neural Networks and Machine Learning - ICANN 2024
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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 VI
Wand, Michael; Schmidhuber, Juergen; Malinovska, Kristina; Tetko, Igor V.
Springer International Publishing AG
10/2024
330
Mole
9783031723469
Pré-lançamento - envio 15 a 20 dias após a sua edição
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.- Multimodality.
.- ARIF: An Adaptive Attention-Based Cross-Modal Representation Integration Framework.
.- BVRCC: Bootstrapping Video Retrieval via Cross-matching Correction.
.- CAW: Confidence-based Adaptive Weighted Model for Multi-modal Entity Linking.
.- Cross-Modal Attention Alignment Network with Auxiliary Text Description for zero-shot sketch-based image retrieva.
.- Exploring Interpretable Semantic Alignment for Multimodal Machine Translation.
.- Modal fusion-Enhanced two-stream hashing network for Cross modal Retrieval.
.- Text Visual Question Answering Based on Interactive Learning and Relationship Modeling.
.- Unifying Visual and Semantic Feature Spaces with Diffusion Models for Enhanced Cross-Modal Alignment.
.- Federated Learning.
.- Addressing the Privacy and Complexity of Urban Traffic Flow Prediction with Federated Learning and Spatiotemporal Graph Convolutional Networks.
.- An Accuracy-Shaping Mechanism for Competitive Distributed Learning.
.- Federated Adversarial Learning for Robust Autonomous Landing Runway Detection.
.- FedInc: One-shot Federated Tuning for Collaborative Incident Recognition.
.- Layer-wised Sparsification Based on Hypernetwork for Distributed NN Training.
.- Security Assessment of Hierarchical Federated Deep Learning.
.- Time Series Processing.
.- ESSformer: Transformers with ESS Attention for Long-Term Series Forecasting.
.- Fusion of image representations for time series classification with deep learning.
.- HierNBeats: Hierarchical Neural Basis Expansion Analysis for Hierarchical Time Series Forecasting.
.- Learning Seasonal-Trend Representations and Conditional Heteroskedasticity for Time Series
Analysis.
.- One Process Spatiotemporal Learning of Transformers via Vcls Token for Multivariate Time Series Forecasting.
.- STformer: Spatio-Temporal Transformer for Multivariate Time Series Anomaly Detection.
.- TF-CL:Time Series Forcasting Based on Time-Frequency Domain Contrastive Learning.
.- ARIF: An Adaptive Attention-Based Cross-Modal Representation Integration Framework.
.- BVRCC: Bootstrapping Video Retrieval via Cross-matching Correction.
.- CAW: Confidence-based Adaptive Weighted Model for Multi-modal Entity Linking.
.- Cross-Modal Attention Alignment Network with Auxiliary Text Description for zero-shot sketch-based image retrieva.
.- Exploring Interpretable Semantic Alignment for Multimodal Machine Translation.
.- Modal fusion-Enhanced two-stream hashing network for Cross modal Retrieval.
.- Text Visual Question Answering Based on Interactive Learning and Relationship Modeling.
.- Unifying Visual and Semantic Feature Spaces with Diffusion Models for Enhanced Cross-Modal Alignment.
.- Federated Learning.
.- Addressing the Privacy and Complexity of Urban Traffic Flow Prediction with Federated Learning and Spatiotemporal Graph Convolutional Networks.
.- An Accuracy-Shaping Mechanism for Competitive Distributed Learning.
.- Federated Adversarial Learning for Robust Autonomous Landing Runway Detection.
.- FedInc: One-shot Federated Tuning for Collaborative Incident Recognition.
.- Layer-wised Sparsification Based on Hypernetwork for Distributed NN Training.
.- Security Assessment of Hierarchical Federated Deep Learning.
.- Time Series Processing.
.- ESSformer: Transformers with ESS Attention for Long-Term Series Forecasting.
.- Fusion of image representations for time series classification with deep learning.
.- HierNBeats: Hierarchical Neural Basis Expansion Analysis for Hierarchical Time Series Forecasting.
.- Learning Seasonal-Trend Representations and Conditional Heteroskedasticity for Time Series
Analysis.
.- One Process Spatiotemporal Learning of Transformers via Vcls Token for Multivariate Time Series Forecasting.
.- STformer: Spatio-Temporal Transformer for Multivariate Time Series Anomaly Detection.
.- TF-CL:Time Series Forcasting Based on Time-Frequency Domain Contrastive Learning.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
artificial intelligence;classification;deep learning;generative models;graph neural networks;image processing;large language models;machine learning;neural networks;reinforcement learning;reservoir computing;robotics;spiking neural networks
.- Multimodality.
.- ARIF: An Adaptive Attention-Based Cross-Modal Representation Integration Framework.
.- BVRCC: Bootstrapping Video Retrieval via Cross-matching Correction.
.- CAW: Confidence-based Adaptive Weighted Model for Multi-modal Entity Linking.
.- Cross-Modal Attention Alignment Network with Auxiliary Text Description for zero-shot sketch-based image retrieva.
.- Exploring Interpretable Semantic Alignment for Multimodal Machine Translation.
.- Modal fusion-Enhanced two-stream hashing network for Cross modal Retrieval.
.- Text Visual Question Answering Based on Interactive Learning and Relationship Modeling.
.- Unifying Visual and Semantic Feature Spaces with Diffusion Models for Enhanced Cross-Modal Alignment.
.- Federated Learning.
.- Addressing the Privacy and Complexity of Urban Traffic Flow Prediction with Federated Learning and Spatiotemporal Graph Convolutional Networks.
.- An Accuracy-Shaping Mechanism for Competitive Distributed Learning.
.- Federated Adversarial Learning for Robust Autonomous Landing Runway Detection.
.- FedInc: One-shot Federated Tuning for Collaborative Incident Recognition.
.- Layer-wised Sparsification Based on Hypernetwork for Distributed NN Training.
.- Security Assessment of Hierarchical Federated Deep Learning.
.- Time Series Processing.
.- ESSformer: Transformers with ESS Attention for Long-Term Series Forecasting.
.- Fusion of image representations for time series classification with deep learning.
.- HierNBeats: Hierarchical Neural Basis Expansion Analysis for Hierarchical Time Series Forecasting.
.- Learning Seasonal-Trend Representations and Conditional Heteroskedasticity for Time Series
Analysis.
.- One Process Spatiotemporal Learning of Transformers via Vcls Token for Multivariate Time Series Forecasting.
.- STformer: Spatio-Temporal Transformer for Multivariate Time Series Anomaly Detection.
.- TF-CL:Time Series Forcasting Based on Time-Frequency Domain Contrastive Learning.
.- ARIF: An Adaptive Attention-Based Cross-Modal Representation Integration Framework.
.- BVRCC: Bootstrapping Video Retrieval via Cross-matching Correction.
.- CAW: Confidence-based Adaptive Weighted Model for Multi-modal Entity Linking.
.- Cross-Modal Attention Alignment Network with Auxiliary Text Description for zero-shot sketch-based image retrieva.
.- Exploring Interpretable Semantic Alignment for Multimodal Machine Translation.
.- Modal fusion-Enhanced two-stream hashing network for Cross modal Retrieval.
.- Text Visual Question Answering Based on Interactive Learning and Relationship Modeling.
.- Unifying Visual and Semantic Feature Spaces with Diffusion Models for Enhanced Cross-Modal Alignment.
.- Federated Learning.
.- Addressing the Privacy and Complexity of Urban Traffic Flow Prediction with Federated Learning and Spatiotemporal Graph Convolutional Networks.
.- An Accuracy-Shaping Mechanism for Competitive Distributed Learning.
.- Federated Adversarial Learning for Robust Autonomous Landing Runway Detection.
.- FedInc: One-shot Federated Tuning for Collaborative Incident Recognition.
.- Layer-wised Sparsification Based on Hypernetwork for Distributed NN Training.
.- Security Assessment of Hierarchical Federated Deep Learning.
.- Time Series Processing.
.- ESSformer: Transformers with ESS Attention for Long-Term Series Forecasting.
.- Fusion of image representations for time series classification with deep learning.
.- HierNBeats: Hierarchical Neural Basis Expansion Analysis for Hierarchical Time Series Forecasting.
.- Learning Seasonal-Trend Representations and Conditional Heteroskedasticity for Time Series
Analysis.
.- One Process Spatiotemporal Learning of Transformers via Vcls Token for Multivariate Time Series Forecasting.
.- STformer: Spatio-Temporal Transformer for Multivariate Time Series Anomaly Detection.
.- TF-CL:Time Series Forcasting Based on Time-Frequency Domain Contrastive Learning.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
