Roy T. Forestano

According to our database, Roy T. Forestano authored at least 17 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2026

Hunting for "Oddballs" with Machine Learning: Detecting Anomalous Exoplanets Using a Deep-Learned Low-Dimensional Representation of Transit Spectra with Autoencoders.

Alexander Roman, Emilie Panek, Roy T. Forestano, Eyup B. Unlu, Katia Matcheva, Konstantin T. Matchev

CoRR, January, 2026

2025

Supervised Machine Learning Methods with Uncertainty Quantification for Exoplanet Atmospheric Retrievals from Transmission Spectroscopy.

Roy T. Forestano, Konstantin T. Matchev, Katia Matcheva, Eyup B. Unlu

CoRR, August, 2025

Quantum-Classical Graph Neural Networks and Jet Tagging.

Haemanth Velmurugan, Roy T. Forestano, Sergei Gleyzer, Kyoungchul Kong, Konstantin T. Matchev, Katia Matcheva

Proceedings of the Quantum Computing and Artificial Intelligence, 2025

2024

Quantum Vision Transformers for Quark-Gluon Classification.

Marçal Comajoan Cara, Gopal Ramesh Dahale, Zhongtian Dong, Roy T. Forestano, Sergei Gleyzer, Daniel Justice, Kyoungchul Kong, Tom Magorsch, Konstantin T. Matchev, Katia Matcheva, Eyup B. Unlu

Axioms, May, 2024

Hybrid Quantum Vision Transformers for Event Classification in High Energy Physics.

Eyup B. Unlu, Marçal Comajoan Cara, Gopal Ramesh Dahale, Zhongtian Dong, Roy T. Forestano, Sergei Gleyzer, Daniel Justice, Kyoungchul Kong, Tom Magorsch, Konstantin T. Matchev, Katia Matcheva

Axioms, March, 2024

A Comparison between Invariant and Equivariant Classical and Quantum Graph Neural Networks.

Roy T. Forestano, Marçal Comajoan Cara, Gopal Ramesh Dahale, Zhongtian Dong, Sergei Gleyzer, Daniel Justice, Kyoungchul Kong, Tom Magorsch, Konstantin T. Matchev, Katia Matcheva, Eyup B. Unlu

Axioms, March, 2024

ℤ2 × ℤ2 Equivariant Quantum Neural Networks: Benchmarking against Classical Neural Networks.

Zhongtian Dong, Marçal Comajoan Cara, Gopal Ramesh Dahale, Roy T. Forestano, Sergei Gleyzer, Daniel Justice, Kyoungchul Kong, Tom Magorsch, Konstantin T. Matchev, Katia Matcheva, Eyup B. Unlu

Axioms, March, 2024

Lie-Equivariant Quantum Graph Neural Networks.

Jogi Suda Neto, Roy T. Forestano, Sergei Gleyzer, Kyoungchul Kong, Konstantin T. Matchev, Katia Matcheva

CoRR, 2024

2023

Oracle-Preserving Latent Flows.

Alexander Roman, Roy T. Forestano, Konstantin T. Matchev, Katia Matcheva, Eyup B. Unlu

Symmetry, July, 2023

Deep learning symmetries and their Lie groups, algebras, and subalgebras from first principles.

Roy T. Forestano, Konstantin T. Matchev, Katia Matcheva, Alexander Roman, Eyup B. Unlu, Sarunas Verner

Mach. Learn. Sci. Technol., June, 2023

Z₂ × Z₂ Equivariant Quantum Neural Networks: Benchmarking against Classical Neural Networks.

Zhongtian Dong, Marçal Comajoan Cara, Gopal Ramesh Dahale, Roy T. Forestano, Sergei Gleyzer, Daniel Justice, Kyoungchul Kong, Tom Magorsch, Konstantin T. Matchev, Katia Matcheva, Eyup B. Unlu

CoRR, 2023

Identifying the Group-Theoretic Structure of Machine-Learned Symmetries.

Roy T. Forestano, Konstantin T. Matchev, Katia Matcheva, Alexander Roman, Eyup B. Unlu, Sarunas Verner

CoRR, 2023

Searching for Novel Chemistry in Exoplanetary Atmospheres using Machine Learning for Anomaly Detection.

Roy T. Forestano, Konstantin T. Matchev, Katia Matcheva, Eyup B. Unlu

CoRR, 2023

Accelerated Discovery of Machine-Learned Symmetries: Deriving the Exceptional Lie Groups G2, F4 and E6.

Roy T. Forestano, Konstantin T. Matchev, Katia Matcheva, Alexander Roman, Eyup B. Unlu, Sarunas Verner

CoRR, 2023

Discovering Sparse Representations of Lie Groups with Machine Learning.

Roy T. Forestano, Konstantin T. Matchev, Katia Matcheva, Alexander Roman, Eyup B. Unlu, Sarunas Verner

CoRR, 2023

Reproducing Bayesian Posterior Distributions for Exoplanet Atmospheric Parameter Retrievals with a Machine Learning Surrogate Model.

Eyup B. Unlu, Roy T. Forestano, Konstantin T. Matchev, Katia Matcheva

Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2023

2021

Lessons Learned from Ariel Data Challenge 2022 - Inferring Physical Properties of Exoplanets From Next-Generation Telescopes.

Kai Hou Yip, Quentin Changeat, Ingo P. Waldmann, Eyup B. Unlu, Roy T. Forestano, Alexander Roman, Katia Matcheva, Konstantin T. Matchev, Stefan Stefanov, Ondrej Podsztavek, Mario Morvan, Nikolaos Nikolaou, Ahmed F. Al-Refaie, Clare Jenner, Chris Johnson, Angelos Tsiaras, Billy Edwards, Catarina Alves de Oliveira, Jeyan Thiyagalingam, Pierre-Olivier Lagage, James Cho, Giovanna Tinetti

Proceedings of the NeurIPS 2022 Competition Track, 2021