Elena Raponi

Orcid: 0000-0001-6841-7409

Affiliations:
  • Leiden University, Leiden Institute of Advanced Computer Science, The Netherlands
  • TU Munich, School of Engineering and Design, Germany (former)
  • University of Camerino, Italy (PhD 2021)
  • Sorbonne Université, Paris, France (former)


According to our database1, Elena Raponi authored at least 27 papers between 2019 and 2026.

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Timeline

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Bibliography

2026
Does Dimensionality Reduction via Random Projections Preserve Landscape Features?
CoRR, April, 2026

MuViS: Multimodal Virtual Sensing Benchmark.
CoRR, March, 2026

Investigating the Interplay of Parameterization and Optimizer in Gradient-Free Topology Optimization: A Cantilever Beam Case Study.
Proceedings of the Applications of Evolutionary Computation - 29th European Conference, 2026

Benchmarking that Matters: Rethinking Benchmarking in Continuous Optimisation for Practical Impact.
Proceedings of the Applications of Evolutionary Computation - 29th European Conference, 2026

2025
Benchmarking that Matters: Rethinking Benchmarking for Practical Impact.
CoRR, November, 2025

MECHBench: A Set of Black-Box Optimization Benchmarks originated from Structural Mechanics.
CoRR, November, 2025

LLaMEA-BO: A Large Language Model Evolutionary Algorithm for Automatically Generating Bayesian Optimization Algorithms.
CoRR, May, 2025

Optimizing With Low Budgets: A Comparison on the Black-Box Optimization Benchmarking Suite and OpenAI Gym.
IEEE Trans. Evol. Comput., February, 2025

Why Are You Wrong? Counterfactual Explanations for Language Grounding with 3D Objects.
Proceedings of the International Joint Conference on Neural Networks, 2025

Optimization Is Not Enough: Why Problem Formulation Deserves Equal Attention.
Proceedings of the Computational Intelligence - 17th International Joint Conference, 2025

EvoCAD: Evolutionary CAD Code Generation with Vision Language Models.
Proceedings of the 37th IEEE International Conference on Tools with Artificial Intelligence, 2025

Cascading CMA-ES Instances for Generating Input-diverse Solution Batches.
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2025

Feasibility-Driven Trust Region Bayesian Optimization.
Proceedings of the International Conference on Automated Machine Learning (AutoML 2025), 2025

2024
Comparison of High-Dimensional Bayesian Optimization Algorithms on BBOB.
ACM Trans. Evol. Learn. Optim., September, 2024

Automated Machine Learning For Computational Mechanics (Dagstuhl Seminar 24282).
Dagstuhl Reports, 2024

Illuminating the Diversity-Fitness Trade-Off in Black-Box Optimization.
CoRR, 2024

Automated Federated Learning via Informed Pruning.
CoRR, 2024

2023
Comparison of Bayesian Optimization Algorithms for BBOB Problems in Dimensions 10 and 60.
Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

Towards Self-Adjusting Weighted Expected Improvement for Bayesian Optimization.
Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

Self-Adjusting Weighted Expected Improvement for Bayesian Optimization.
Proceedings of the International Conference on Automated Machine Learning, 2023

2022
GSAreport: Easy to Use Global Sensitivity Reporting.
J. Open Source Softw., October, 2022

Towards Automated Design of Bayesian Optimization via Exploratory Landscape Analysis.
CoRR, 2022

PI is back! Switching Acquisition Functions in Bayesian Optimization.
CoRR, 2022

A Comparison of Global Sensitivity Analysis Methods for Explainable AI With an Application in Genomic Prediction.
IEEE Access, 2022

High Dimensional Bayesian Optimization with Kernel Principal Component Analysis.
Proceedings of the Parallel Problem Solving from Nature - PPSN XVII, 2022

2020
High Dimensional Bayesian Optimization Assisted by Principal Component Analysis.
Proceedings of the Parallel Problem Solving from Nature - PPSN XVI, 2020

2019
Hybrid Kriging-assisted Level Set Method for Structural Topology Optimization.
Proceedings of the 11th International Joint Conference on Computational Intelligence, 2019


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