Konstantin T. Matchev

According to our database, Konstantin T. Matchev authored at least 25 papers between 2018 and 2024.

Collaborative distances:

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

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

Quantum Diffusion Model for Quark and Gluon Jet Generation.

Mariia Baidachna, Rey Guadarrama, Gopal Ramesh Dahale, Tom Magorsch, Isabel Pedraza, Konstantin T. Matchev, Katia Matcheva, Kyoungchul Kong, Sergei Gleyzer

CoRR, 2024

Lie-Equivariant Quantum Graph Neural Networks.

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

CoRR, 2024

Quantum Attention for Vision Transformers in High Energy Physics.

Alessandro Tesi, Gopal Ramesh Dahale, Sergei Gleyzer, Kyoungchul Kong, Tom Magorsch, Konstantin T. Matchev, Katia Matcheva

CoRR, 2024

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

Konstantin T. Matchev, Katia Matcheva, Pierre Ramond, Sarunas Verner

CoRR, 2024

2023

Oracle-Preserving Latent Flows.

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

Symmetry, July, 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

Seeking Truth and Beauty in Flavor Physics with Machine Learning.

Konstantin T. Matchev, Katia Matcheva, Pierre Ramond, Sarunas Verner

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

Deep Learning Symmetries and Their Lie Groups, Algebras, and Subalgebras from First Principles.

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

2022

InClass nets: independent classifier networks for nonparametric estimation of conditional independence mixture models and unsupervised classification.

Konstantin T. Matchev, Prasanth Shyamsundar

Mach. Learn. Sci. Technol., 2022

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

Zhongtian Dong, Kyoungchul Kong, Konstantin T. Matchev, Katia Matcheva

CoRR, 2022

New Machine Learning Techniques for Simulation-Based Inference: InferoStatic Nets, Kernel Score Estimation, and Kernel Likelihood Ratio Estimation.

Kyoungchul Kong, Konstantin T. Matchev, Stephen Mrenna, Prasanth Shyamsundar

CoRR, 2022

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

Konstantin T. Matchev, Katia Matcheva, Alexander Roman

CoRR, 2022

2021

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

Konstantin T. Matchev, Katia Matcheva, Alexander Roman

CoRR, 2021

Deep-Learned Event Variables for Collider Phenomenology.

Doojin Kim, Kyoungchul Kong, Konstantin T. Matchev, Myeonghun Park, Prasanth Shyamsundar

CoRR, 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

2018

LHC collider phenomenology of minimal universal extra dimensions.

Jyotiranjan Beuria, AseshKrishna Datta, Dipsikha Debnath, Konstantin T. Matchev

Comput. Phys. Commun., 2018