Michelle Girvan

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 17

Top Topics

Recurrent Neural Networks

Reservoir Computing

Data Assimilation

Top Venues

Neural Networks

SN Comput. Sci.

Publications

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 (2024)
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 (2024)
Alexander Wikner, Brian R. Hunt, Joseph Harvey, Michelle Girvan, Edward Ott
Stabilizing Machine Learning Prediction of Dynamics: Noise and Noise-inspired Regularization. CoRR (2022)
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) (2022)
Daniel Canaday, Andrew Pomerance, Michelle Girvan
A Meta-learning Approach to Reservoir Computing: Time Series Prediction with Limited Data. CoRR (2021)
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 (2021)
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 (2021)
Matthew Evanusa, Snehesh Shrestha, Michelle Girvan, Cornelia Fermüller, Yiannis Aloimonos
Hybrid Backpropagation Parallel Reservoir Networks. CoRR (2020)
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 (2020)
Pantelis R. 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 (2020)
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)
David Darmon, William Rand, Michelle Girvan
Computational landscape of user behavior on social media. CoRR (2019)
Pantelis R. 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 (2019)
Sanjukta Krishnagopal, Michelle Girvan, Edward Ott, Brian R. Hunt
Separation of Chaotic Signals by Reservoir Computing. CoRR (2019)
Sanjukta Krishnagopal, Yiannis Aloimonos, Michelle Girvan
Similarity Learning and Generalization with Limited Data: A Reservoir Computing Approach. Complex. 2018 (2018)
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 (2018)
Keith Burghardt, Emanuel F. Alsina, Michelle Girvan, William Rand, Kristina Lerman
The Myopia of Crowds: A Study of Collective Evaluation on Stack Exchange. CoRR (2016)
Kimberly Glass, Michelle Girvan
Finding New Order in Biological Functions from the Network Structure of Gene Annotations. PLoS Comput. Biol. 11 (11) (2015)
David Darmon, Michelle Girvan
Complexity-Regularized Regression for Serially-Correlated Residuals with Applications to Stock Market Data. Entropy 17 (1) (2015)
Jimpei Harada, David Darmon, Michelle Girvan, William Rand
Forecasting High Tide: Predicting Times of Elevated Activity in Online Social Media. ASONAM (2015)
Andrew Melchionna, Jesus Caloca, Shane Squires, Thomas M. Antonsen Jr., Edward Ott, Michelle Girvan
The Impact of Imperfect Information on Network Attack. CoRR (2014)
Keith Burghardt, William Rand, Michelle Girvan
Competing Opinions and Stubborness: Connecting Models to Data. CoRR (2014)
Ari Zitin, Alex Gorowora, Shane Squires, Mark Herrera, Thomas M. Antonsen Jr., Michelle Girvan, Edward Ott
Spatially embedded growing small-world networks. CoRR (2013)
John Platig, Edward Ott, Michelle Girvan
Robustness of Network Measures to Link Errors. CoRR (2013)
David Darmon, Jared Sylvester, Michelle Girvan, William Rand
Predictability of User Behavior in Social Media: Bottom-Up v. Top-Down Modeling. SocialCom (2013)
David Darmon, Jared Sylvester, Michelle Girvan, William Rand
Predictability of User Behavior in Social Media: Bottom-Up v. Top-Down Modeling. CoRR (2013)
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)