Results 11 to 20 of about 4,928 (26)
On the Topic of Jets: Disentangling Quarks and Gluons at Colliders [PDF]
, 2018 We introduce jet topics: a framework to identify underlying classes of jets from collider data. Because of a close mathematical relationship between distributions of observables in jets and emergent themes in sets of documents, we can apply recent ...
Metodiev, Eric M., Thaler, Jesse
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Modelling conditional probabilities with Riemann-Theta Boltzmann Machines [PDF]
, 2019 The probability density function for the visible sector of a Riemann-Theta Boltzmann machine can be taken conditional on a subset of the visible units. We derive that the corresponding conditional density function is given by a reparameterization of the ...
Carrazza, Stefano +2 more
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Event Generation and Statistical Sampling for Physics with Deep Generative Models and a Density Information Buffer [PDF]
, 2019 We present a study for the generation of events from a physical process with deep generative models. The simulation of physical processes requires not only the production of physical events, but also to ensure these events occur with the correct ...
Caron, Sascha +8 more
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Adversarial attacks hidden in plain sight
, 2020 Convolutional neural networks have been used to achieve a string of successes during recent years, but their lack of interpretability remains a serious issue.
DLK Yamins +4 more
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Machine learning challenges in theoretical HEP [PDF]
, 2017 In these proceedings we perform a brief review of machine learning (ML) applications in theoretical High Energy Physics (HEP-TH). We start the discussion by defining and then classifying machine learning tasks in theoretical HEP.
Carrazza, Stefano
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, 2017 The precise modeling of subatomic particle interactions and propagation through matter is paramount for the advancement of nuclear and particle physics searches and precision measurements.
de Oliveira, Luke +2 more
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Unsupervised Learning via Total Correlation Explanation [PDF]
, 2017 Learning by children and animals occurs effortlessly and largely without obvious supervision. Successes in automating supervised learning have not translated to the more ambiguous realm of unsupervised learning where goals and labels are not provided ...
Steeg, Greg Ver
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, 2017 Physicists at the Large Hadron Collider (LHC) rely on detailed simulations of particle collisions to build expectations of what experimental data may look like under different theory modeling assumptions. Petabytes of simulated data are needed to develop
de Oliveira, Luke +2 more
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Learning to Generate Images with Perceptual Similarity Metrics
, 2017 Deep networks are increasingly being applied to problems involving image synthesis, e.g., generating images from textual descriptions and reconstructing an input image from a compact representation.
Liao, Renjie +5 more
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, 2019 Computational materials screening studies require fast calculation of the properties of thousands of materials. The calculations are often performed with Density Functional Theory (DFT), but the necessary computer time sets limitations for the ...
del Río, Estefanía Garijo +3 more
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