952 citations · 3.4k across the 79 of their papers we have counts for
6 papers · 1 filter
Adaptive Divergence for Rapid Adversarial Optimization
Maxim Borisyak, Tatiana Gaintseva, Andrey Ustyuzhanin
Adversarial Optimization (AO) provides a reliable, practical way to match two implicitly defined distributions, one of which is usually represented by a sample of real data, and th…
-class Classification: an Anomaly Detection Method for Highly Imbalanced or Incomplete Data Sets
Maxim Borisyak, Artem Ryzhikov, Andrey Ustyuzhanin +3
Anomaly detection is not an easy problem since distribution of anomalous samples is unknown a priori. We explore a novel method that gives a trade-off possibility between one-class…
Fast Data-Driven Simulation of Cherenkov Detectors Using Generative Adversarial Networks
Artem Maevskiy, Denis Derkach, Nikita Kazeev +3
The increasing luminosities of future Large Hadron Collider runs and next generation of collider experiments will require an unprecedented amount of simulated events to be produced…
The Tracking Machine Learning challenge : Accuracy phase
Sabrina Amrouche, Laurent Basara, Paolo Calafiura +24
This paper reports the results of an experiment in high energy physics: using the power of the "crowd" to solve difficult experimental problems linked to tracking accurately the tr…
Cherenkov Detectors Fast Simulation Using Neural Networks
Denis Derkach, Nikita Kazeev, Fedor Ratnikov +2
We propose a way to simulate Cherenkov detector response using a generative adversarial neural network to bypass low-level details. This network is trained to reproduce high level…
Space Navigator: a Tool for the Optimization of Collision Avoidance Maneuvers
Leonid Gremyachikh, Dmitrii Dubov, Nikita Kazeev +6
The number of space objects will grow several times in a few years due to the planned launches of constellations of thousands microsatellites. It leads to a significant increase in…