{"product_id":"computational-intelligence-ebook","title":"Computational Intelligence","description":"\u003cp\u003e\u003cstrong\u003e.- International Conference on Explainable AI for Neural and Symbolic Methods.\u003c\/strong\u003e\u003cbr\u003e.- AutoCausalAIME: A CMA-ES-Driven Framework for Parametric\u003cbr\u003ePenalty Tuning in Causal Inverse Explanations.\u003cbr\u003e.- Leveraging Large Language Models for Generating and Evaluating Natural Language Explanations in XAI: A Comparative Study.\u003cbr\u003e.- Uncertainty in Deep Model Performance for Radiology: A Case Study of Classifying Maxillary Sinus Appearance.\u003cbr\u003e.- Explain to Gain: Optimising Performance Through Explainable Reinforcement Learning Parameter Investigation.\u003cbr\u003e.- Quantifying Prototype Stability in ProtoPNet Without Manual Part Annotations.\u003cbr\u003e.- Interpretable Railway Object Classification Using Part-Prototype Networks.\u003cbr\u003e.- Efficient Construction of Interpretable Oblique Decision Trees.\u003cbr\u003e.- Extracting Deterministic Finite Automata from RNNs via Hyperplane Partitioning and Learning.\u003cbr\u003e.- Profiling German Text Simplification with Model-Fingerprints.\u003cbr\u003e.- Attention Maps in 3D Shape Classification for Dental Stage Estimation with Class Node Graph Attention Networks.\u003cbr\u003e.- Extensibility, Model Interpretability and Explainability, and Automation in ML.NET: A Comprehensive Analysis.\u003cbr\u003e.- SemantriX: An Explainable Hybrid Model for Aligning Vector Similarity and Semantic Relevance.\u003cbr\u003e.- Explainable Knowledge Access: Recursive and Rerank-Based RAG for Interpretable QA.\u003cbr\u003e.- How Prompting Shapes Decisions: Analyzing LLM Behavior in XAI-Augmented Decision Support Systems.\u003cbr\u003e.- Mechanistic Interpretability for Transformer-based Time Series Classification.\u003cbr\u003e.- XAI-Driven Solutions to Enhance Safety for Limited-Mobility Road Users.\u003cbr\u003e.- User Fairness in Recommender Systems using Beyond-Accuracy Basket Quality Metrics.\u003cbr\u003e.- Analyzing Accuracy and Consistency of GPT 4o Mini in Trivial Pursuit, and the Implications for its Use in Professional Contexts.\u003cbr\u003e.- Interpretable Explainable AI: Comparing Bayesian Structural Equation Modelling with Other Algorithms.\u003cbr\u003e.- Unsupervised Hierarchical Growing Neural Architecture for Sensorimotor Map Learning.\u003cbr\u003e.- Rule Extraction from Fake News Classifiers.\u003cbr\u003e.- Contrasting Human and Emergent Concepts in Image Classifiers.\u003cbr\u003e.- An Explainable Multi-Domain Document Summarization Framework using Domain-Aware Fine-Tuned Large Language Models.\u003cbr\u003e.- SPAX: A Shapley-Based Point Attribution eXplanation for Interpreting 3D Point Cloud Classification.\u003cbr\u003e.- A Privacy-Preserving and Explainable Approach for Anomaly Detection in Substation Networks.\u003cbr\u003e.- Exposing Shortcuts in Image Classification by Aggregating Counterfactuals.\u003cbr\u003e.- On Explainable Disease Progression Forecasting with Transformer Models.\u003cbr\u003e\u003cstrong\u003e.- International Conference on Neural Computation Theory and Applications.\u003c\/strong\u003e\u003cbr\u003e.- Determining Optimal Pixel Resolution for Object Detection in Satellite Imagery: A Class-Specific Approach.\u003cbr\u003e.- Re-Ranked Transformer: New Strategy Based on Misspellings and Typos Pattern Analysis for Keystroke Biometrics Improvement.\u003cbr\u003e.- Towards Generalizing Deep Reinforcement Learning Algorithms for Real World Applications.\u003cbr\u003e.- Degradation-Aware Energy Management in Residential Microgrids: A Reinforcement Learning Framework.\u003cbr\u003e.- Innovative Techniques for Efficient Hyperdimensional Computing on Hardware: Enhance Accuracy and On-Fly Hypervector Generation.\u003cbr\u003e.- A Universal Urban Electricity-Demand Simulator for Developing and Evaluating Load-Scheduling and Forecasting Systems.\u003cbr\u003e.- Drowsiness Detection with Time-Series Classification Using HRV Features.\u003cbr\u003e.- A Structured Survey of Anomaly Types and Classification-Based Detection Models in IoT.\u003cbr\u003e.- Assessing Driving Style from Telematics Data with a Two-Stage Clustering Approach.\u003cbr\u003e.- Fine-Tuning Prototypes for Cross-Domain Few-Shot Image Classification Using Contrastive Objective.\u003cbr\u003e.- OS-QLR: One-Shot Quantized Latent Refinement for Fast and Efficient Image Generation.\u003cbr\u003e.- Dataset-Independent Approach for Generating Synthetic Data in Optical Defect Detection.\u003cbr\u003e.- Combining Large-Scale and Domain-Specific Datasets for Hate Speech Severity Modeling: A Regression-Based Approach.\u003cbr\u003e.- MLP Model for Prediction of Pellet Combustion: How to Deal with Small Datasets.\u003cbr\u003e.- Multi-Subspace SVD Generators for Continual Learning.\u003cbr\u003e.- From High-Frequency Sensors to Noon Reports: Using Transfer Learning for Shaft Power Prediction in Maritime.\u003cbr\u003e.- Towards Robust Urban Parking Violation Prediction Using Graph Kolmogorov–Arnold Networks and Liquid Neural Networks.\u003cbr\u003e.- Data Augmentation for Neuroaesthetics Analysis.\u003c\/p\u003e","brand":"Francesco Marcelloni","offers":[{"title":"Default Title","offer_id":53658038206791,"sku":"9783032156389","price":96.29,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0920\/5455\/2903\/files\/computational-intelligence-ebook-cover.webp?v=1775483481","url":"https:\/\/www.cinebuch.de\/products\/computational-intelligence-ebook","provider":"CineBuch","version":"1.0","type":"link"}