Katia Matcheva

Orcid: 0000-0003-3074-998X

According to our database1, Katia Matcheva authored at least 27 papers between 2021 and 2026.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
ASTER - Agentic Science Toolkit for Exoplanet Research.
CoRR, March, 2026

The Pareto Frontiers of Magic and Entanglement: The Case of Two Qubits.
CoRR, March, 2026

AI Agents for Variational Quantum Circuit Design.
CoRR, February, 2026

Hunting for "Oddballs" with Machine Learning: Detecting Anomalous Exoplanets Using a Deep-Learned Low-Dimensional Representation of Transit Spectra with Autoencoders.
CoRR, January, 2026

2025
Supervised Machine Learning Methods with Uncertainty Quantification for Exoplanet Atmospheric Retrievals from Transmission Spectroscopy.
CoRR, August, 2025

Quantum-Classical Graph Neural Networks and Jet Tagging.
Proceedings of the Quantum Computing and Artificial Intelligence, 2025

Quantum Attention for Vision Transformers in High Energy Physics.
Proceedings of the Quantum Computing and Artificial Intelligence, 2025

2024
Quantum Vision Transformers for Quark-Gluon Classification.
Axioms, May, 2024

Hybrid Quantum Vision Transformers for Event Classification in High Energy Physics.
Axioms, March, 2024

A Comparison between Invariant and Equivariant Classical and Quantum Graph Neural Networks.
Axioms, March, 2024

ℤ2 × ℤ2 Equivariant Quantum Neural Networks: Benchmarking against Classical Neural Networks.
Axioms, March, 2024

Quantum Diffusion Model for Quark and Gluon Jet Generation.
CoRR, 2024

Lie-Equivariant Quantum Graph Neural Networks.
CoRR, 2024

Exploring the Truth and Beauty of Theory Landscapes with Machine Learning.
CoRR, 2024

2023
Oracle-Preserving Latent Flows.
Symmetry, July, 2023

Deep learning symmetries and their Lie groups, algebras, and subalgebras from first principles.
Mach. Learn. Sci. Technol., June, 2023

Z<sub>2</sub> × Z<sub>2</sub> Equivariant Quantum Neural Networks: Benchmarking against Classical Neural Networks.
CoRR, 2023

Seeking Truth and Beauty in Flavor Physics with Machine Learning.
CoRR, 2023

Identifying the Group-Theoretic Structure of Machine-Learned Symmetries.
CoRR, 2023

Searching for Novel Chemistry in Exoplanetary Atmospheres using Machine Learning for Anomaly Detection.
CoRR, 2023

Accelerated Discovery of Machine-Learned Symmetries: Deriving the Exceptional Lie Groups G2, F4 and E6.
CoRR, 2023

Discovering Sparse Representations of Lie Groups with Machine Learning.
CoRR, 2023

Reproducing Bayesian Posterior Distributions for Exoplanet Atmospheric Parameter Retrievals with a Machine Learning Surrogate Model.
Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2023

2022
Is the Machine Smarter than the Theorist: Deriving Formulas for Particle Kinematics with Symbolic Regression.
CoRR, 2022

Unsupervised Machine Learning for Exploratory Data Analysis of Exoplanet Transmission Spectra.
CoRR, 2022

2021
Analytical Modelling of Exoplanet Transit Specroscopy with Dimensional Analysis and Symbolic Regression.
CoRR, 2021



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