activity
20132022
most citedDeep Temporal Clustering : Fully Unsupervised Learning of Time-Domain Features

107 citations · 360 across the 13 of their papers we have counts for

collaborators

13 papers

physics.plasm-ph2022★ 2 cited

Hybrid codes (massless electron fluid)

D. Winske, Homa Karimabadi, Ari Le +3

Hybrid codes are widely used to model ion-scale phenomena in space plasmas. Hybrid codes differ from full particle (PIC) codes in that the electrons are modeled as a fluid that is…

physics.space-ph2020★ 6 cited

Major Scientific Challenges and Opportunities in Understanding Magnetic Reconnection and Related Explosive Phenomena in Solar and Heliospheric Plasmas

H. Ji, J. Karpen, A. Alt +105

Magnetic reconnection underlies many explosive phenomena in the heliosphere and in laboratory plasmas. The new research capabilities in theory/simulations, observations, and labora…

cs.LG2020★ 1 cited

Instance Explainable Temporal Network For Multivariate Timeseries

Naveen Madiraju, Homa Karimabadi

Although deep networks have been widely adopted, one of their shortcomings has been their blackbox nature. One particularly difficult problem in machine learning is multivariate ti…

physics.plasm-ph2020★ 5 cited

Major Scientific Challenges and Opportunities in Understanding Magnetic Reconnection and Related Explosive Phenomena throughout the Universe

H. Ji, A. Alt, S. Antiochos +97

This white paper summarizes major scientific challenges and opportunities in understanding magnetic reconnection and related explosive phenomena as a fundamental plasma process.

physics.plasm-ph2019★ 3 cited

Challenges and the next transformative steps in understanding plasma turbulence from the perspective of multi-spacecraft measurements

Li-Jen Chen, Naoki Bessho, Jay A. Bookbinder +18

We have become heavily reliant on electrical technologies, from power grids to GPS to wireless communication. Any disruption of these systems will have severe global consequences.…

physics.plasm-ph2018★ 7 cited

Wavelet Methods for Studying the Onset of Strong Plasma Turbulence

Ari Le, Vadim Roytershteyn, Homa Karimabadi +3

Wavelet basis functions are a natural tool for analyzing turbulent flows containing localized coherent structures of different spatial scales. Here, wavelets are used to study the…