Publications | Artificial Intelligence National Laboratory

Ensemble Bag-of-Audio-Words Representation Improves Paralinguistic Classification Accuracy

Gábor Gosztolya

Busa-Fekete Róbert

Tovább

Fooling a Complete Neural Network Verifier

Dániel Zombori

Balázs Bánhelyi

Tibor Csendes

István Megyeri

Márk Jelasity

Tovább

HierarchyNet: Hierarchical CNN-Based Urban Building Classification

Taoufiq S

Balázs Nagy

Csaba Benedek

Tovább

Traits versus Grades : The predictive power of psychological factors and pre-enrollment achievement measures on academic performance.

Séllei Beatrix

Stumphauser Nóra

Roland Molontay

Tovább

FoBSim: an extensible open-source simulation tool for integrated fog-blockchain systems

Baniata Hamza

Attila Kertész

Tovább

Comparing the effectiveness of two remedial mathematics courses using modern regression discontinuity techniques

Máté Baranyi

Roland Molontay

Tovább

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

Tovább

Deep Learning-Based Masonry Wall Image Analysis

Ibrahim Y

Nagy Balázs

Benedek Csaba

Tovább

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

Nagy Marcell

Roland Molontay

Tovább

Publikációk

Ensemble Bag-of-Audio-Words Representation Improves Paralinguistic Classification Accuracy

Fooling a Complete Neural Network Verifier

HierarchyNet: Hierarchical CNN-Based Urban Building Classification

Traits versus Grades : The predictive power of psychological factors and pre-enrollment achievement measures on academic performance.

FoBSim: an extensible open-source simulation tool for integrated fog-blockchain systems

Comparing the effectiveness of two remedial mathematics courses using modern regression discontinuity techniques

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

Deep Learning-Based Masonry Wall Image Analysis

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

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