Search Results for author:
Found 8 papers, 6 papers with code
Assessment of few-hits machine learning classification algorithms for low energy physics in liquid argon detectors
The physics potential of massive liquid argon TPCs in the low-energy regime is still to be fully reaped because few-hits events encode information that can hardly be exploited by conventional classification algorithms.
Segmentation of glioblastomas in early post-operative multi-modal MRI with deep neural networks
The current standard method for estimating it is subject to high inter- and intra-rater variability, and an automated method for segmentation of residual tumor in early post-operative MRI could lead to a more accurate estimation of extent of resection.
ChaCha for Online AutoML
We propose the ChaCha (Champion-Challengers) algorithm for making an online choice of hyperparameters in online learning settings.
Deep Learning strategies for ProtoDUNE raw data denoising
In this work, we investigate different machine learning-based strategies for denoising raw simulation data from the ProtoDUNE experiment.
PDFFlow: hardware accelerating parton density access
We present PDFFlow, a new software for fast evaluation of parton distribution functions (PDFs) designed for platforms with hardware accelerators.
Resonance: Replacing Software Constants with Context-Aware Models in Real-time Communication
Large software systems tune hundreds of 'constants' to optimize their runtime performance.
PDFFlow: parton distribution functions on GPU
We present PDFFlow, a new software for fast evaluation of parton distribution functions (PDFs) designed for platforms with hardware accelerators.
Analytical and cellular automaton approach to a generalized SEIR model for infection spread in an open crowded space
We formulate a generalized susceptible exposed infectious recovered (SEIR) model on a graph, describing the population dynamics of an open crowded place with an arbitrary topology.
Physics and Society Populations and Evolution
