4 papers
Weak lensing cosmology with convolutional neural networks on noisy data
Dezső Ribli, Bálint Ármin Pataki, José Manuel Zorrilla Matilla +3
Weak gravitational lensing is one of the most promising cosmological probes of the late universe. Several large ongoing (DES, KiDS, HSC) and planned (LSST, EUCLID, WFIRST) astronom…
Galaxy shape measurement with convolutional neural networks
Dezső Ribli, László Dobos, István Csabai
We present our results from training and evaluating a convolutional neural network (CNN) to predict galaxy shapes from wide-field survey images of the first data release of the Dar…
An improved cosmological parameter inference scheme motivated by deep learning
Dezső Ribli, Bálint Ármin Pataki, István Csabai
Dark matter cannot be observed directly, but its weak gravitational lensing slightly distorts the apparent shapes of background galaxies, making weak lensing one of the most promis…
Detecting and classifying lesions in mammograms with Deep Learning
Dezső Ribli, Anna Horváth, Zsuzsa Unger +2
In the last two decades Computer Aided Diagnostics (CAD) systems were developed to help radiologists analyze screening mammograms. The benefits of current CAD technologies appear t…