Thiago Rios

According to our database, Thiago Rios authored at least 16 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

LLM2FEA: Discover Novel Designs with Generative Evolutionary Multitasking.

Melvin Wong, Jiao Liu, Thiago Rios, Stefan Menzel, Yew Soon Ong

CoRR, 2024

Generative AI-based Prompt Evolution Engineering Design Optimization With Vision-Language Model.

Melvin Wong, Thiago Rios, Stefan Menzel, Yew Soon Ong

CoRR, 2024

Prompt Evolutionary Design Optimization with Generative Shape and Vision-Language models.

Melvin Wong, Thiago Rios, Stefan Menzel, Yew Soon Ong

Proceedings of the IEEE Congress on Evolutionary Computation, 2024

2023

Large Language and Text-to-3D Models for Engineering Design Optimization.

Thiago Rios, Stefan Menzel, Bernhard Sendhoff

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2023

2022

Multitask Shape Optimization Using a 3-D Point Cloud Autoencoder as Unified Representation.

Thiago Rios, Bas van Stein, Thomas Bäck, Bernhard Sendhoff, Stefan Menzel

IEEE Trans. Evol. Comput., 2022

2021

Exploiting Generative Models for Performance Predictions of 3D Car Designs.

Sneha Saha, Thiago Rios, Leandro L. Minku, Bas van Stein, Patricia Wollstadt, Xin Yao, Thomas Bäck, Bernhard Sendhoff, Stefan Menzel

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2021

Exploiting Local Geometric Features in Vehicle Design Optimization with 3D Point Cloud Autoencoders.

Thiago Rios, Bas van Stein, Patricia Wollstadt, Thomas Bäck, Bernhard Sendhoff, Stefan Menzel

Proceedings of the IEEE Congress on Evolutionary Computation, 2021

Point2FFD: Learning Shape Representations of Simulation-Ready 3D Models for Engineering Design Optimization.

Thiago Rios, Bas van Stein, Thomas Bäck, Bernhard Sendhoff, Stefan Menzel

Proceedings of the International Conference on 3D Vision, 2021

2020

On the Performance of Oversampling Techniques for Class Imbalance Problems.

Jiawen Kong, Thiago Rios, Wojtek Kowalczyk, Stefan Menzel, Thomas Bäck

Dataset, May, 2020

Back To Meshes: Optimal Simulation-ready Mesh Prototypes For Autoencoder-based 3D Car Point Clouds.

Thiago Rios, Jiawen Kong, Bas van Stein, Thomas Bäck, Patricia Wollstadt, Bernhard Sendhoff, Stefan Menzel

Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

On the Performance of Oversampling Techniques for Class Imbalance Problems.

Jiawen Kong, Thiago Rios, Wojtek Kowalczyk, Stefan Menzel, Thomas Bäck

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2020

Feature Visualization for 3D Point Cloud Autoencoders.

Thiago Rios, Bas van Stein, Stefan Menzel, Thomas Bäck, Bernhard Sendhoff, Patricia Wollstadt

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

2019

Optimal Evolutionary Optimization Hyper-parameters to Mimic Human User Behavior.

Sneha Saha, Thiago Rios, Leandro L. Minku, Xin Yao, Zhao Xu, Bernhard Sendhoff, Stefan Menzel

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2019

Scalability of Learning Tasks on 3D CAE Models Using Point Cloud Autoencoders.

Thiago Rios, Patricia Wollstadt, Bas van Stein, Thomas Bäck, Zhao Xu, Bernhard Sendhoff, Stefan Menzel

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2019

On the Efficiency of a Point Cloud Autoencoder as a Geometric Representation for Shape Optimization.

Thiago Rios, Bernhard Sendhoff, Stefan Menzel, Thomas Bäck, Bas van Stein

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2019

Learning Time-Series Data of Industrial Design Optimization using Recurrent Neural Networks.

Sneha Saha, Thiago Rios, Stefan Menzel, Bernhard Sendhoff, Thomas Bäck, Xin Yao, Zhao Xu, Patricia Wollstadt

Proceedings of the 2019 International Conference on Data Mining Workshops, 2019