{"total":19,"rows":[{"id":"2305.13998","title":"SMT 2.0: A Surrogate Modeling Toolbox with a focus on Hierarchical and Mixed Variables Gaussian Processes","created":"2023-05-23","cited_by_count":29,"area":null},{"id":"2311.06130","title":"High-dimensional mixed-categorical Gaussian processes with application to multidisciplinary design optimization for a green aircraft","created":"2023-11-10","cited_by_count":8,"area":null},{"id":"2510.16742","title":"Surrogate Modeling and Explainable Artificial Intelligence for Complex Systems: A Workflow for Automated Simulation Exploration","created":"2025-10-19","cited_by_count":6,"area":null},{"id":"2405.13073","title":"A distance for mixed-variable and hierarchical domains with meta variables","created":"2024-05-20","cited_by_count":5,"area":null},{"id":"2503.19496","title":"SMT-EX: An Explainable Surrogate Modeling Toolbox for Mixed-Variables Design Exploration","created":"2025-03-25","cited_by_count":4,"area":null},{"id":"2504.09930","title":"Multi-objective Bayesian Optimization With Mixed-categorical Design Variables for Expensive-to-evaluate Aeronautical Applications","created":"2025-04-14","cited_by_count":4,"area":null},{"id":"2506.22621","title":"Modeling Hierarchical Spaces: A Review and Unified Framework for Surrogate-Based Architecture Design","created":"2025-06-27","cited_by_count":4,"area":null},{"id":"2503.19479","title":"Bayesian Optimization of a Lightweight and Accurate Neural Network for Aerodynamic Performance Prediction","created":"2025-03-25","cited_by_count":3,"area":null},{"id":"2504.08721","title":"Surrogate-based optimization of system architectures subject to hidden constraints","created":"2025-04-11","cited_by_count":3,"area":null},{"id":"2506.04813","title":"Distributional encoding for Gaussian process regression with qualitative inputs","created":"2025-06-05","cited_by_count":1,"area":null},{"id":"2507.08715","title":"System-of-systems Modeling and Optimization: An Integrated Framework for Intermodal Mobility","created":"2025-07-11","cited_by_count":1,"area":null},{"id":"2503.02630","title":"Weighted Euclidean Distance Matrices over Mixed Continuous and Categorical Inputs for Gaussian Process Models","created":"2025-03-04","cited_by_count":0,"area":null},{"id":"2507.09694","title":"Frequency-aware Surrogate Modeling With SMT Kernels For Advanced Data Forecasting","created":"2025-07-13","cited_by_count":0,"area":null},{"id":"2512.11946","title":"Global Sensitivity Analysis for Engineering Design Based on Individual Conditional Expectations","created":"2025-12-12","cited_by_count":0,"area":null},{"id":"2603.28987","title":"Multi-fidelity approaches for general constrained Bayesian optimization with application to aircraft design","created":"2026-03-30","cited_by_count":0,"area":null},{"id":"2603.28999","title":"Transfer Learning in Bayesian Optimization for Aircraft Design","created":"2026-03-30","cited_by_count":0,"area":null},{"id":"2605.20989","title":"Modeling Temporal scRNA-seq Data with Latent Gaussian Process and Optimal Transport","created":"2026-05-20","cited_by_count":0,"area":null},{"id":"2607.22560","title":"Efficient multidisciplinary design via Bayesian optimization","created":"2026-05-28","cited_by_count":0,"area":null},{"id":"2609.22130","title":"Hierarchical Bayesian optimization of an aircraft-based multi-agent system-of-systems","created":"2026-08-23","cited_by_count":0,"area":null}],"next_cursor":null}