7 citations · 7 across the 2 of their papers we have counts for
6 papers
Cosmic Background Removal with Deep Neural Networks in SBND
SBND Collaboration, R. Acciarri, C. Adams +128
In liquid argon time projection chambers exposed to neutrino beams and running on or near surface levels, cosmic muons and other cosmic particles are incident on the detectors whil…
Neural networks adapting to datasets: learning network size and topology
Romuald A. Janik, Aleksandra Nowak
We introduce a flexible setup allowing for a neural network to learn both its size and topology during the course of a standard gradient-based training. The resulting network has t…
Analyzing Neural Networks Based on Random Graphs
Romuald A. Janik, Aleksandra Nowak
We perform a massive evaluation of neural networks with architectures corresponding to random graphs of various types. We investigate various structural and numerical properties of…
WICA: nonlinear weighted ICA
Andrzej Bedychaj, Przemysław Spurek, Aleksandra Nowak +1
Independent Component Analysis (ICA) aims to find a coordinate system in which the components of the data are independent. In this paper we construct a new nonlinear ICA model, cal…
Non-linear ICA based on Cramer-Wold metric
Przemysław Spurek, Aleksandra Nowak, Jacek Tabor +2
Non-linear source separation is a challenging open problem with many applications. We extend a recently proposed Adversarial Non-linear ICA (ANICA) model, and introduce Cramer-Wold…
Set Aggregation Network as a Trainable Pooling Layer
Łukasz Maziarka, Marek Śmieja, Aleksandra Nowak +3
Global pooling, such as max- or sum-pooling, is one of the key ingredients in deep neural networks used for processing images, texts, graphs and other types of structured data. Bas…