| Nome |
# |
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Marine safety and data analytics: Vessel crash stop maneuvering performance prediction, file e268c4ca-7b76-a6b7-e053-3a05fe0adea1
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264
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Deep graph node kernels: A convex approach, file e268c4ca-8479-a6b7-e053-3a05fe0adea1
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245
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Human Movement Datasets: An Interdisciplinary Scoping Review, file 0538477e-a18b-4426-aa04-4eab1f918446
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186
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Fairness in Machine Learning, file e268c4cd-9c1b-a6b7-e053-3a05fe0adea1
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177
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Delay prediction system for large-scale railway networks based on big data analytics, file e268c4ca-1b18-a6b7-e053-3a05fe0adea1
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164
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ReForeSt: Random forests in apache spark, file e268c4ca-829d-a6b7-e053-3a05fe0adea1
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123
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Unintrusive Monitoring of Induction Motors Bearings via Deep Learning on Stator Currents, file e268c4ca-7a00-a6b7-e053-3a05fe0adea1
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93
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Marine dual fuel engines monitoring in the wild through weakly supervised data analytics, file e268c4cf-0a1f-a6b7-e053-3a05fe0adea1
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88
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Advances in artificial neural networks, machine learning and computational intelligence, file e268c4ce-bd57-a6b7-e053-3a05fe0adea1
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86
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Optimizing Fuel Consumption in Thrust Allocation for Marine Dynamic Positioning Systems, file e268c4ce-f654-a6b7-e053-3a05fe0adea1
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69
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Randomized learning and generalization of fair and private classifiers: From PAC-Bayes to stability and differential privacy, file e268c4cd-9c0e-a6b7-e053-3a05fe0adea1
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59
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Towards Online Discovery of Data-Aware Declarative Process Models from Event Streams, file e268c4cd-6094-a6b7-e053-3a05fe0adea1
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45
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Physical and Data-Driven Models Hybridisation for Modelling the Dynamic State of a Four-Stroke Marine Diesel Engine, file e268c4ce-8d9e-a6b7-e053-3a05fe0adea1
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43
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The benefits of adversarial defense in generalization, file 602b0c28-642b-487d-a5de-2735abe2b388
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34
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Deep Learning for the Generation of Heuristics in Answer Set Programming: A Case Study of Graph Coloring, file 79acf9c0-ab88-4c71-8de8-30cee1818338
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33
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Digital Twin of the Mooring Line Tension for Floating Offshore Wind Turbines, file e268c4cf-1c3d-a6b7-e053-3a05fe0adea1
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32
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In-Station Train Dispatching: A PDDL+ Planning Approach, file e268c4cf-074d-a6b7-e053-3a05fe0adea1
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30
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Predicting the cavitating marine propeller noise at design stage: A deep learning based approach, file e268c4cc-5861-a6b7-e053-3a05fe0adea1
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29
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Advances in artificial neural networks, machine learning and computational intelligence, file e268c4cd-608c-a6b7-e053-3a05fe0adea1
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27
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Numerical methods for monitoring and evaluating the biofouling state and effects on vessels’ hull and propeller performance: A review, file e268c4ce-b966-a6b7-e053-3a05fe0adea1
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24
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Floating Spar-Type Offshore Wind Turbine Hydrodynamic Response Characterisation: A Computational Cost Aware Approach, file e268c4cf-098f-a6b7-e053-3a05fe0adea1
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24
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Natural language processing for aviation safety: Extracting knowledge from publicly-available loss of separation reports, file 66fba470-115d-4bfc-ad61-1dc59bfea28e
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21
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Random Forests model selection, file e268c4ca-7b6f-a6b7-e053-3a05fe0adea1
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16
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Measuring the expressivity of graph kernels through the rademacher complexity, file e268c4ca-7a04-a6b7-e053-3a05fe0adea1
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14
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Computationally aware estimation of ultimate strength reduction of stiffened panels caused by welding residual stress: From finite element to data-driven methods, file 5b12a027-b6ff-4130-93a1-6a9291861475
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13
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An Efficient Hybrid Planning Framework for In-Station Train Dispatching, file e268c4cf-10f3-a6b7-e053-3a05fe0adea1
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13
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Tuning the distribution dependent prior in the PAC-Bayes framework based on empirical data, file e268c4ca-7b71-a6b7-e053-3a05fe0adea1
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11
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Advances in learning with kernels: Theory and practice in a world of growing constraints, file e268c4ca-82b0-a6b7-e053-3a05fe0adea1
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11
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Understanding Violin Players’ Skill Level Based on Motion Capture: a Data-Driven Perspective, file e268c4cd-6090-a6b7-e053-3a05fe0adea1
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11
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Digital twins of the mooring line tension for floating offshore wind turbines to improve monitoring, lifespan, and safety, file e268c4ce-bd53-a6b7-e053-3a05fe0adea1
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11
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Data analytics and clinical feature ranking of medical records of patients with sepsis, file e268c4cf-18d7-a6b7-e053-3a05fe0adea1
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10
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Physically plausible propeller noise prediction via recursive corrections leveraging prior knowledge and experimental data, file 827bb91c-5673-4be4-9e33-2b9d8632efad
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9
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A Planning-based Approach for In-Station Train Dispatching, file e268c4cf-031f-a6b7-e053-3a05fe0adea1
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9
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Toward learning trustworthily from data combining privacy, fairness, and explainability: An application to face recognition, file e268c4cf-1292-a6b7-e053-3a05fe0adea1
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9
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Complex Data: Learning Trustworthily, Automatically, and with Guarantees, file e268c4ce-a4a6-a6b7-e053-3a05fe0adea1
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8
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Physical, data-driven and hybrid approaches to model engine exhaust gas temperatures in operational conditions, file e268c4cf-10f5-a6b7-e053-3a05fe0adea1
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8
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In-Station Train Movements Prediction: from Shallow to Deep Multi Scale Models, file e268c4ce-f656-a6b7-e053-3a05fe0adea1
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7
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Communication platform concept for virtual testing of novel applications for railway traffic management systems, file e268c4ce-f6c1-a6b7-e053-3a05fe0adea1
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7
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Improving the union bound: A distribution dependent approach, file e268c4cf-09e2-a6b7-e053-3a05fe0adea1
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7
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Eleven quick tips for data cleaning and feature engineering, file be0cb0d2-1688-4077-a8ce-9256494d769b
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6
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Prescriptive maintenance of railway infrastructure: From data analytics to decision support, file e268c4cc-3243-a6b7-e053-3a05fe0adea1
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6
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Computational Prediction of Propeller Cavitation Noise, file e268c4cd-d1b4-a6b7-e053-3a05fe0adea1
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5
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The Benefits of Adversarial Defence in Generalisation, file e268c4ce-f658-a6b7-e053-3a05fe0adea1
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5
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A review on ship motions and quiescent periods prediction models, file 42111f3f-950f-4aeb-bdb0-4a46aa7e8869
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4
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Surrogate models to unlock the optimal design of stiffened panels accounting for ultimate strength reduction due to welding residual stress, file 4413c90a-60e2-4caa-89b1-9c82328efc22
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4
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Traffic Characterization for a Dynamic and Adaptive Trajectory Prediction Data-Driven Approach, file 91e34179-4b54-4f6f-a169-1ba6af7f1e72
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4
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Fair Empirical Risk Minimization Revised, file c7681190-4ff6-41b0-90d7-a5284d44ec17
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4
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Introduzione al Progetto di Sistemi Digitali, file e268c4c9-66d4-a6b7-e053-3a05fe0adea1
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4
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Fair regression via plug-in estimator and recalibration, file e268c4cf-025c-a6b7-e053-3a05fe0adea1
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4
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Learning deep fair graph neural networks, file e268c4cf-0a27-a6b7-e053-3a05fe0adea1
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4
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Exploiting MMD and sinkhorn divergences for fair and transferable representation learning, file e268c4cf-15e4-a6b7-e053-3a05fe0adea1
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4
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DAYDREAMS - Development of Prescriptive Analytics based on Artificial Intelligence for Railways Intelligent Abet Management Systems, file b8a94824-31a7-435b-a76d-1eeb88c036c7
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3
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Train Delay Prediction Systems: A Big Data Analytics Perspective, file e268c4c9-d189-a6b7-e053-3a05fe0adea1
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3
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Fair regression with wasserstein barycenters, file e268c4cf-0a24-a6b7-e053-3a05fe0adea1
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3
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Artificial Intelligence-based short-term forecasting of vessel performance parameters, file 2627c950-05f9-431e-9b1a-3a428a4c7c18
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2
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Short-term Forecast and Long-term Simulation for Accurate Energy Consumption Prediction, file 41366230-9f48-4eb2-8e02-11eacb0dce4f
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2
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On the problem of recommendation for sensitive users and influential items: Simultaneously maintaining interest and diversity, file 7bd319ca-2b54-416a-aa2d-ff3ca128b892
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2
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Do we really need a new theory to understand over-parameterization?, file 81f29181-394d-4cf6-8a2a-ece6e09b05af
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2
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Artificial Intelligence Based Short-Term Motions Forecasting for Autonomous Marine Vehicles Control, file 83551cad-8ad1-4eb0-a23a-da6772c447b9
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2
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A Non-deterministic propeller design optimization framework leveraging machine learning based boundary element methods surrogates, file 9a293fd4-f820-4f7b-9be3-1802feaea475
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2
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Advances in artificial neural networks, machine learning and computational intelligence, file c336681d-1be9-43f2-8adf-1d8ca7b30c0f
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2
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Simple Non Regressive Informed Machine Learning Model for Prescriptive Maintenance of Track Circuits in a Subway Environment, file d259366e-fa0b-4d8b-b1de-f291fb57441f
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2
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Low-Resource Footprint, Data-Driven Malware Detection on Android, file e268c4c8-3bfd-a6b7-e053-3a05fe0adea1
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2
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Statistical Learning Theory and ELM for Big Social Data Analysis, file e268c4c9-c0ac-a6b7-e053-3a05fe0adea1
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2
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Transition-Aware Human Activity Recognition Using Smartphones, file e268c4c9-ceb0-a6b7-e053-3a05fe0adea1
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2
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Dynamic delay predictions for large-scale railway networks: Deep and shallow extreme learning machines tuned via thresholdout, file e268c4c9-d18c-a6b7-e053-3a05fe0adea1
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2
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Global Rademacher Complexity Bounds: From Slow to Fast Convergence Rates, file e268c4c9-d193-a6b7-e053-3a05fe0adea1
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2
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Data-Driven Photovoltaic Power Production Nowcasting and Forecasting for Polygeneration Microgrids, file e268c4c9-d3df-a6b7-e053-3a05fe0adea1
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2
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Support vector machines and strictly positive definite kernel: The regularization hyperparameter is more important than the kernel hyperparameters, file e268c4ca-29e0-a6b7-e053-3a05fe0adea1
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2
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Data driven models for propeller cavitation noise in model scale, file e268c4ca-5c8c-a6b7-e053-3a05fe0adea1
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2
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Cavitation Noise Spectra Prediction with Hybrid Models, file e268c4ca-7464-a6b7-e053-3a05fe0adea1
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2
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Quantum computing and supervised machine learning: Training, model selection, and error estimation, file e268c4ca-7b6a-a6b7-e053-3a05fe0adea1
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2
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Data-driven ship digital twin for estimating the speed loss caused by the marine fouling, file e268c4cb-ee43-a6b7-e053-3a05fe0adea1
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2
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Determining the most influential human factors in maritime accidents: A data-driven approach, file e268c4cd-42da-a6b7-e053-3a05fe0adea1
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2
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PAC-Bayes Theory, file e268c4cd-42e4-a6b7-e053-3a05fe0adea1
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2
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General Fair Empirical Risk Minimization, file e268c4cd-9c14-a6b7-e053-3a05fe0adea1
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2
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Preface, file e268c4cd-9c1d-a6b7-e053-3a05fe0adea1
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2
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Identifying the determinants of innovation capability with machine learning and patents, file e268c4ce-8d9c-a6b7-e053-3a05fe0adea1
|
2
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Towards learning trustworthily, automatically, and with guarantees on graphs: An overview, file e268c4ce-a60a-a6b7-e053-3a05fe0adea1
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2
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Distribution-dependent weighted union bound, file e268c4cf-0322-a6b7-e053-3a05fe0adea1
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2
|
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Computational intelligence identifies alkaline phosphatase (Alp), alpha-fetoprotein (afp), and hemoglobin levels as most predictive survival factors for hepatocellular carcinoma, file e268c4cf-18d5-a6b7-e053-3a05fe0adea1
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2
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Data-driven Underwater Radiated Noise Modelling of Cavitating Marine Propellers, file e350981e-c3e9-49ca-b4b8-80265465e56b
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2
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Simple Non Regressive Informed Machine Learning Model for Prescriptive Maintenance of Track Circuits in a Subway Environment, file 042904dc-04ae-43a2-b634-2b369de75854
|
1
|
|
Untargeted LC-HRMS Based-Plasma Metabolomics Reveals 3-O-Methyldopa as a New Biomarker of Poor Prognosis in High-Risk Neuroblastoma, file 24f5f81e-50c1-46f4-8d3e-ae5c674b0c52
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1
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Data science and advanced analytics for shipping energy systems, file 560be012-7358-444d-9e0e-12ea2d00385d
|
1
|
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The Importance of Multiple Temporal Scales in Motion Recognition: when Shallow Model can Support Deep Multi Scale Models, file 7936809e-2173-43aa-9e28-a3dc691c82c3
|
1
|
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The Importance of Multiple Temporal Scales in Motion Recognition: from Shallow to Deep Multi Scale Models, file 816804d7-33e4-4a2c-b67d-68db801f098a
|
1
|
|
Innovation Capability of Firms: A Big Data Approach with Patents, file 90c85f74-01bd-4efe-933e-25ed799914a1
|
1
|
|
Computational prediction of underwater radiated noise of cavitating marine propellers: On the accuracy of semi-empirical models, file bcaeef9e-24d0-4b2d-8b0a-3b938bfa6faa
|
1
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Toward new generation railway Traffic Management Systems: the contribution of the OPTIMA project, file d09afff4-0fc3-4ffe-bf90-2c374c4a98f4
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1
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Learning Resource-Aware Classifiers for Mobile Devices: From Regularization to Energy Efficiency, file e268c4c6-a19c-a6b7-e053-3a05fe0adea1
|
1
|
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Condition-based maintenance of naval propulsion systems: Data analysis with minimal feedback, file e268c4c9-9df3-a6b7-e053-3a05fe0adea1
|
1
|
|
Learning With Kernels: A Local Rademacher Complexity-Based Analysis With Application to Graph Kernels, file e268c4c9-a19a-a6b7-e053-3a05fe0adea1
|
1
|
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Differential privacy and generalization: Sharper bounds with applications, file e268c4c9-beca-a6b7-e053-3a05fe0adea1
|
1
|
|
A local Vapnik-Chervonenkis complexity, file e268c4c9-beda-a6b7-e053-3a05fe0adea1
|
1
|
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Semi-supervised Learning for Affective Common-Sense Reasoning, file e268c4c9-c0aa-a6b7-e053-3a05fe0adea1
|
1
|
|
PAC-bayesian analysis of distribution dependent priors: Tighter risk bounds and stability analysis, file e268c4c9-c0ae-a6b7-e053-3a05fe0adea1
|
1
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Learning Hardware-Friendly Classifiers through Algorithmic Stability, file e268c4c9-c0ba-a6b7-e053-3a05fe0adea1
|
1
|
|
Can machine learning explain human learning?, file e268c4c9-c0c0-a6b7-e053-3a05fe0adea1
|
1
|
|
Measuring the expressivity of graph kernels through Statistical Learning Theory, file e268c4c9-d191-a6b7-e053-3a05fe0adea1
|
1
|
| Totale |
2.207 |