Mandar Chandorkar
Mandar Chandorkar
Data Scientist, Connecterra
Verified email at connecterra.io - Homepage
Title
Cited by
Cited by
Year
Probabilistic forecasting of the disturbance storm time index: An autoregressive Gaussian process approach
M Chandorkar, E Camporeale, S Wing
Space Weather 15 (8), 1004-1019, 2017
202017
Multiple-hour-ahead forecast of the Dst index using a combination of long short-term memory neural network and Gaussian process
MA Gruet, M Chandorkar, A Sicard, E Camporeale
Space Weather 16 (11), 1882-1896, 2018
182018
On the propagation of uncertainties in radiation belt simulations
E Camporeale, Y Shprits, M Chandorkar, A Drozdov, S Wing
Space Weather 14 (11), 982-992, 2016
92016
Fixed-size least squares support vector machines: Scala implementation for large scale classification
M Chandorkar, R Mall, O Lauwers, JAK Suykens, B De Moor
2015 IEEE Symposium Series on Computational Intelligence, 522-528, 2015
52015
Probabilistic forecasting of geomagnetic indices using Gaussian process models
M Chandorkar, E Camporeale
Machine learning techniques for space weather, 237-258, 2018
32018
Dynamic Time Lag Regression: Predicting What & When
M Chandorkar, C Furtlehner, B Poduval, E Camporeale, M Sebag
International Conference on Learning Representations, 2019
22019
Fixed Size Least Squares Support Vector Machines: A Scala based programming framework for Large Scale Classification
M Chandorkar
Katholieke Universiteit Leuven, 2015
22015
Bayesian inference of radiation belt loss timescales.
E Camporeale, M Chandorkar
AGUFM 2017, SM23A-2583, 2017
12017
Gaussian Process Models for One Hour Ahead Prediction of the Dst Index.
M Chandorkar, E Camporeale, S Wing
AGUFM, SH11C-2261, 2016
12016
Bayesian Inference of Quasi‐Linear Radial Diffusion Parameters using Van Allen Probes
R Sarma, M Chandorkar, I Zhelavskaya, Y Shprits, A Drozdov, ...
Journal of Geophysical Research: Space Physics 125 (5), e2019JA027618, 2020
2020
Dynamic Time Lag Regression: Predicting Time Lagged Effects of Solar Activity
M Chandorkar, E Camporeale, B Poduval, C Furthlener, M Sebag
AGU Fall Meeting 2019, 2019
2019
A Deep Learning Approach to Forecast Tomorrow's Solar Wind Parameters.
C Shneider, E Camporeale, M Chandorkar
AGUFM 2019, NG31A-0837, 2019
2019
Dynamic Time Lag Regression: Predicting Time Lagged Effects of Solar Activity
B Poduval, M Chandorkar, E Camporeale, C Furthlener, M Sebag
AGUFM 2019, NG22A-05, 2019
2019
Machine Learning in Space Weather
M Chandorkar
Université of Eindhoven, 2019
2019
Machine learning in space weather: forecasting, identification and uncertainty quantification
MH Chandorkar
2019
Identification of Radial Diffusion Parameters for the Earth's Radiation Belt through Bayesian Inference.
R Sarma, M Chandorkar, E Camporeale, A Drozdov, Y Shprits
Geophysical Research Abstracts 21, 2019
2019
Bayesian Inference of Radial Diffusion Parameters for the Earth's Radiation Belt: a Deep Learning Framework
R Sarma, M Chandorkar, E Camporeale, A Drozdov, Y Shprits
AGU Fall Meeting 2018, 2018
2018
A Deep Learning Approach To Forecast
C Shneider, MH Chandorkar, M Bobra, E Camporeale
2018
Bayesian Inference of Radial Diffusion Parameters for the Earth's Radiation Belt: a Deep Learning Framework
E Camporeale, R Sarma, M Chandorkar, A Drozdov, Y Shprits
AGUFM 2018, SM31D-3515, 2018
2018
Predicting Time Lagged Effects of Solar Disturbances from Heliospheric Images: A Deep Learning Approach
M Chandorkar, E Camporeale, C Furthlener, M Sebag
AGUFM 2018, SM54A-04, 2018
2018
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