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06/01/2023
Towards Foundation Models for Scientific Machine Learning: Characterizing Scaling and Transfer Behavior
Pre-trained machine learning (ML) models have shown great performance fo...
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05/09/2022
Long-term stability and generalization of observationally-constrained stochastic data-driven models for geophysical turbulence
Recent years have seen a surge in interest in building deep learning-bas...
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05/26/2021
The Petascale DTN Project: High Performance Data Transfer for HPC Facilities
The movement of large-scale (tens of Terabytes and larger) data sets bet...
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02/13/2020
The use of Convolutional Neural Networks for signal-background classification in Particle Physics experiments
The success of Convolutional Neural Networks (CNNs) in image classificat...
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07/08/2019
Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale
Probabilistic programming languages (PPLs) are receiving widespread atte...
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09/17/2018
Graph Neural Networks for IceCube Signal Classification
Tasks involving the analysis of geometric (graph- and manifold-structure...
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07/20/2018
Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model
We present a novel framework that enables efficient probabilistic infere...
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07/08/2018
Machine Learning in High Energy Physics Community White Paper
Machine learning is an important research area in particle physics, begi...
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12/21/2017
Improvements to Inference Compilation for Probabilistic Programming in Large-Scale Scientific Simulators
We consider the problem of Bayesian inference in the family of probabili...
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11/09/2017
Deep Neural Networks for Physics Analysis on low-level whole-detector data at the LHC
There has been considerable recent activity applying deep convolutional ...
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08/17/2017
Deep Learning at 15PF: Supervised and Semi-Supervised Classification for Scientific Data
This paper presents the first, 15-PetaFLOP Deep Learning system for solv...
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01/28/2016
