Wahid Bhimji | DeepAI

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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...

0 Shashank Subramanian, et al. ∙

∙ 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...

5 Ashesh Chattopadhyay, et al. ∙

∙ 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...

0 Eli Dart, et al. ∙

∙ 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...

3 Venkitesh Ayyar, et al. ∙

∙ 07/08/2019

Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale

Probabilistic programming languages (PPLs) are receiving widespread atte...

2 Atılım Güneş Baydin, et al. ∙

∙ 09/17/2018

Graph Neural Networks for IceCube Signal Classification

Tasks involving the analysis of geometric (graph- and manifold-structure...

2 Nicholas Choma, et al. ∙

∙ 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...

4 Atilim Gunes Baydin, et al. ∙

∙ 07/08/2018

Machine Learning in High Energy Physics Community White Paper

Machine learning is an important research area in particle physics, begi...

0 Kim Albertsson, et al. ∙

∙ 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...

0 Mario Lezcano Casado, et al. ∙

∙ 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 ...

0 Wahid Bhimji, et al. ∙

∙ 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...

0 Thorsten Kurth, et al. ∙

∙ 01/28/2016

Revealing Fundamental Physics from the Daya Bay Neutrino Experiment using Deep Neural Networks

Experiments in particle physics produce enormous quantities of data that...

0 Evan Racah, et al. ∙

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