16 citations · 16 across the 6 of their papers we have counts for
6 papers
Hybrid Quantum Vision Transformers for Event Classification in High Energy Physics
Eyup B. Unlu, Marçal Comajoan Cara, Gopal Ramesh Dahale +8
Models based on vision transformer architectures are considered state-of-the-art when it comes to image classification tasks. However, they require extensive computational resource…
Reproducing Bayesian Posterior Distributions for Exoplanet Atmospheric Parameter Retrievals with a Machine Learning Surrogate Model
Eyup B. Unlu, Roy T. Forestano, Konstantin T. Matchev +1
We describe a machine-learning-based surrogate model for reproducing the Bayesian posterior distributions for exoplanet atmospheric parameters derived from transmission spectra of…
Identifying the Group-Theoretic Structure of Machine-Learned Symmetries
Roy T. Forestano, Konstantin T. Matchev, Katia Matcheva +3
Deep learning was recently successfully used in deriving symmetry transformations that preserve important physics quantities. Being completely agnostic, these techniques postpone t…
Searching for Novel Chemistry in Exoplanetary Atmospheres using Machine Learning for Anomaly Detection
Roy T. Forestano, Konstantin T. Matchev, Katia Matcheva +1
The next generation of telescopes will yield a substantial increase in the availability of high-resolution spectroscopic data for thousands of exoplanets. The sheer volume of data…
Oracle-Preserving Latent Flows
Alexander Roman, Roy T. Forestano, Konstantin T. Matchev +2
We develop a deep learning methodology for the simultaneous discovery of multiple nontrivial continuous symmetries across an entire labelled dataset. The symmetry transformations a…
Deep Learning Symmetries and Their Lie Groups, Algebras, and Subalgebras from First Principles
Roy T. Forestano, Konstantin T. Matchev, Katia Matcheva +3
We design a deep-learning algorithm for the discovery and identification of the continuous group of symmetries present in a labeled dataset. We use fully connected neural networks…