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Michelle Girvan
Person information
- affiliation: University of Maryland, College Park, USA
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2020 – today
- 2024
- [j6]Alexander Wikner
, Joseph Harvey, Michelle Girvan, Brian R. Hunt, Andrew Pomerance
, Thomas M. Antonsen Jr.
, Edward Ott:
Stabilizing machine learning prediction of dynamics: Novel noise-inspired regularization tested with reservoir computing. Neural Networks 170: 94-110 (2024) - [i17]Ravi Chepuri, Dael Amzalag, Thomas M. Antonsen Jr., Michelle Girvan:
Hybridizing Traditional and Next-Generation Reservoir Computing to Accurately and Efficiently Forecast Dynamical Systems. CoRR abs/2403.18953 (2024) - 2022
- [j5]Matthew Evanusa
, Snehesh Shrestha, Vaishnavi Patil, Cornelia Fermüller, Michelle Girvan, Yiannis Aloimonos:
Deep-Readout Random Recurrent Neural Networks for Real-World Temporal Data. SN Comput. Sci. 3(3): 222 (2022) - [i16]Alexander Wikner, Brian R. Hunt, Joseph Harvey, Michelle Girvan, Edward Ott:
Stabilizing Machine Learning Prediction of Dynamics: Noise and Noise-inspired Regularization. CoRR abs/2211.05262 (2022) - 2021
- [i15]Alexander Wikner, Jaideep Pathak, Brian R. Hunt, Istvan Szunyogh, Michelle Girvan, Edward Ott:
Using Data Assimilation to Train a Hybrid Forecast System that Combines Machine-Learning and Knowledge-Based Components. CoRR abs/2102.07819 (2021) - [i14]Keshav Srinivasan, Nolan Coble, Joy Hamlin, Thomas M. Antonsen Jr., Edward Ott, Michelle Girvan:
Parallel Machine Learning for Forecasting the Dynamics of Complex Networks. CoRR abs/2108.12129 (2021) - [i13]Daniel Canaday, Andrew Pomerance, Michelle Girvan:
A Meta-learning Approach to Reservoir Computing: Time Series Prediction with Limited Data. CoRR abs/2110.03722 (2021) - 2020
- [j4]Pantelis-Rafail Vlachas
, Jaideep Pathak, Brian R. Hunt, Themistoklis P. Sapsis, Michelle Girvan, Edward Ott, Petros Koumoutsakos
:
Backpropagation algorithms and Reservoir Computing in Recurrent Neural Networks for the forecasting of complex spatiotemporal dynamics. Neural Networks 126: 191-217 (2020) - [i12]Alexander Wikner, Jaideep Pathak, Brian R. Hunt, Michelle Girvan, Troy Arcomano, Istvan Szunyogh, Andrew Pomerance, Edward Ott:
Combining Machine Learning with Knowledge-Based Modeling for Scalable Forecasting and Subgrid-Scale Closure of Large, Complex, Spatiotemporal Systems. CoRR abs/2002.05514 (2020) - [i11]Matthew Evanusa, Snehesh Shrestha, Michelle Girvan, Cornelia Fermüller, Yiannis Aloimonos:
Hybrid Backpropagation Parallel Reservoir Networks. CoRR abs/2010.14611 (2020)
2010 – 2019
- 2019
- [c4]Sanjukta Krishnagopal, Garrett E. Katz, Michelle Girvan, James A. Reggia:
Encoding of a Chaotic Attractor in a Reservoir Computer: A Directional Fiber Investigation. IJCNN 2019: 1-8 - [i10]David Darmon, William Rand, Michelle Girvan:
Computational landscape of user behavior on social media. CoRR abs/1901.08941 (2019) - [i9]Pantelis-Rafail Vlachas, Jaideep Pathak, Brian R. Hunt, Themistoklis P. Sapsis, Michelle Girvan, Edward Ott, Petros Koumoutsakos:
Forecasting of Spatio-temporal Chaotic Dynamics with Recurrent Neural Networks: a comparative study of Reservoir Computing and Backpropagation Algorithms. CoRR abs/1910.05266 (2019) - [i8]Sanjukta Krishnagopal, Michelle Girvan, Edward Ott, Brian R. Hunt:
Separation of Chaotic Signals by Reservoir Computing. CoRR abs/1910.10080 (2019) - 2018
- [j3]Sanjukta Krishnagopal
, Yiannis Aloimonos, Michelle Girvan:
Similarity Learning and Generalization with Limited Data: A Reservoir Computing Approach. Complex. 2018: 6953836:1-6953836:15 (2018) - [i7]Jaideep Pathak, Alexander Wikner, Rebeckah Fussell, Sarthak Chandra, Brian R. Hunt, Michelle Girvan, Edward Ott:
Hybrid Forecasting of Chaotic Processes: Using Machine Learning in Conjunction with a Knowledge-Based Model. CoRR abs/1803.04779 (2018) - 2016
- [i6]Keith Burghardt, Emanuel F. Alsina, Michelle Girvan, William Rand, Kristina Lerman:
The Myopia of Crowds: A Study of Collective Evaluation on Stack Exchange. CoRR abs/1602.07388 (2016) - 2015
- [j2]David Darmon, Michelle Girvan:
Complexity-Regularized Regression for Serially-Correlated Residuals with Applications to Stock Market Data. Entropy 17(1): 1-27 (2015) - [j1]Kimberly Glass
, Michelle Girvan:
Finding New Order in Biological Functions from the Network Structure of Gene Annotations. PLoS Comput. Biol. 11(11) (2015) - [c3]Jimpei Harada, David Darmon, Michelle Girvan
, William Rand
:
Forecasting High Tide: Predicting Times of Elevated Activity in Online Social Media. ASONAM 2015: 504-507 - 2014
- [i5]Keith Burghardt, William Rand, Michelle Girvan:
Competing Opinions and Stubborness: Connecting Models to Data. CoRR abs/1411.7415 (2014) - [i4]Andrew Melchionna, Jesus Caloca, Shane Squires, Thomas M. Antonsen Jr., Edward Ott, Michelle Girvan:
The Impact of Imperfect Information on Network Attack. CoRR abs/1412.3204 (2014) - 2013
- [c2]Hao Wang, Geet Duggal, Rob Patro, Michelle Girvan, Sridhar Hannenhalli, Carl Kingsford:
Topological properties of chromosome conformation graphs reflect spatial proximities within chromatin. BCB 2013: 306 - [c1]David Darmon, Jared Sylvester, Michelle Girvan, William Rand
:
Predictability of User Behavior in Social Media: Bottom-Up v. Top-Down Modeling. SocialCom 2013: 102-107 - [i3]David Darmon, Jared Sylvester, Michelle Girvan, William Rand:
Predictability of User Behavior in Social Media: Bottom-Up v. Top-Down Modeling. CoRR abs/1306.6111 (2013) - [i2]John Platig, Edward Ott, Michelle Girvan:
Robustness of Network Measures to Link Errors. CoRR abs/1309.4720 (2013) - [i1]Ari Zitin, Alex Gorowora, Shane Squires, Mark Herrera, Thomas M. Antonsen Jr., Michelle Girvan, Edward Ott:
Spatially embedded growing small-world networks. CoRR abs/1312.7165 (2013)
Coauthor Index
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last updated on 2024-08-05 20:19 CEST by the dblp team
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