Publications

The efficient and accurate characterization of the robustness of neural networks to input perturbation is an important open problem. Many approaches exist including heuristic and exact (or complete) methods. Complete methods are expensive but their mathem

Zsolt János Viharos

Kis K B

Fodor Á

Büki M Á

Deep learning identification for citizen science surveillance of tiger mosquitoes

Bálint Armin Pataki

Joan Garriga

Roger Eritja

John R. B. Palmer

Frederic Bartumeus

István Csabai

Large Scale Evaluation of Natural Language Processing Based Test-to-Code Traceability Approaches

András Kicsi

Viktor Csuvik

László Vidács

Exact Distribution-Free Hypothesis Tests for the Regression Function of Binary Classification via Conditional Kernel Mean Embeddings

Ambrus Tamás

Balázs Csanád Csáji

Identifying Conflict Escalation and Primates by Using Ensemble X-Vectors and Fisher Vector Features

José Vicente Egas-López

Mercedes Vetráb

László Tóth

Gábor Gosztolya

Deep Learning-Based Masonry Wall Image Analysis

Ibrahim Y

Nagy Balázs

Benedek Csaba

Is cardiac involvement prevalent in highly trained athletes after SARS-CoV-2 infection? A cardiac magnetic resonance study using sex-matched and age-matched controls

Liliána Szabó

Vencel Juhász

Zsófia Dohy

Csenge Fogarasi

Attila Kovács

Bálint K. Lakatos

Orsolya Kiss

Nóra Sydó

Emese Csulak

Ferenc Imre Suhai

Kristóf Hirschberg

Dávid Becker

Béla Merkely

Hajnalka Vágó

Comprehensive analysis of the predictive validity of the university entrance score in Hungary

Nagy Marcell

Roland Molontay

Impact of periprocedural morphine use on mortality in STEMI patients treated with primary PCI

Dominika Domokos

András Szabó

Gyöngyvér Bánhegyi

László Major

Róbert Gábor Kiss

Dávid Becker

István Ferenc Édes

Zoltán Ruzsa