Michelle Girvan

31 papers B 2Journal 26Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Boosting Reservoir Computing with Brain-inspired Adaptive Dynamics. CoRR Keshav Srinivasan, Dietmar Plenz, Michelle Girvan
2025	J	`jnl`	Learning Beyond Experience: Generalizing to Unseen State Space with Reservoir Computing. CoRR Declan A. Norton, Yuanzhao Zhang, Michelle Girvan
2025	J	`jnl`	Tailored Forecasting from Short Time Series via Meta-learning. CoRR Declan A. Norton, Edward Ott, Andrew Pomerance, Brian R. Hunt, Michelle Girvan
2024	J	`jnl`	Hybridizing Traditional and Next-Generation Reservoir Computing to Accurately and Efficiently Forecast Dynamical Systems. CoRR Ravi Chepuri, Dael Amzalag, Thomas M. Antonsen Jr., Michelle Girvan
2024	J	`jnl`	Stabilizing machine learning prediction of dynamics: Novel noise-inspired regularization tested with reservoir computing. Neural Networks Alexander Wikner, Joseph Harvey, Michelle Girvan, Brian R. Hunt, Andrew Pomerance, Thomas M. Antonsen Jr., Edward Ott
2023	—	`conf`	t-ConvESN: Temporal Convolution-Readout for Random Recurrent Neural Networks. ICANN (6) Matthew S. Evanusa, Vaishnavi Patil, Michelle Girvan, Joel Goodman, Cornelia Fermüller, Yiannis Aloimonos
2022	J	`jnl`	Deep-Readout Random Recurrent Neural Networks for Real-World Temporal Data. SN Comput. Sci. Matthew Evanusa, Snehesh Shrestha, Vaishnavi Patil, Cornelia Fermüller, Michelle Girvan, Yiannis Aloimonos
2022	J	`jnl`	Stabilizing Machine Learning Prediction of Dynamics: Noise and Noise-inspired Regularization. CoRR Alexander Wikner, Brian R. Hunt, Joseph Harvey, Michelle Girvan, Edward Ott
2021	J	`jnl`	A Meta-learning Approach to Reservoir Computing: Time Series Prediction with Limited Data. CoRR Daniel Canaday, Andrew Pomerance, Michelle Girvan
2021	J	`jnl`	Parallel Machine Learning for Forecasting the Dynamics of Complex Networks. CoRR Keshav Srinivasan, Nolan J. Coble, Joy Hamlin, Thomas M. Antonsen Jr., Edward Ott, Michelle Girvan
2021	J	`jnl`	Using Data Assimilation to Train a Hybrid Forecast System that Combines Machine-Learning and Knowledge-Based Components. CoRR Alexander Wikner, Jaideep Pathak, Brian R. Hunt, Istvan Szunyogh, Michelle Girvan, Edward Ott
2020	J	`jnl`	Backpropagation algorithms and Reservoir Computing in Recurrent Neural Networks for the forecasting of complex spatiotemporal dynamics. Neural Networks Pantelis-Rafail Vlachas, Jaideep Pathak, Brian R. Hunt, Themistoklis P. Sapsis, Michelle Girvan, Edward Ott, Petros Koumoutsakos
2020	J	`jnl`	Combining Machine Learning with Knowledge-Based Modeling for Scalable Forecasting and Subgrid-Scale Closure of Large, Complex, Spatiotemporal Systems. CoRR Alexander Wikner, Jaideep Pathak, Brian R. Hunt, Michelle Girvan, Troy Arcomano, Istvan Szunyogh, Andrew Pomerance, Edward Ott
2020	J	`jnl`	Hybrid Backpropagation Parallel Reservoir Networks. CoRR Matthew Evanusa, Snehesh Shrestha, Michelle Girvan, Cornelia Fermüller, Yiannis Aloimonos
2019	J	`jnl`	Computational landscape of user behavior on social media. CoRR David Darmon, William Rand, Michelle Girvan
2019	B	`conf`	Encoding of a Chaotic Attractor in a Reservoir Computer: A Directional Fiber Investigation. IJCNN Sanjukta Krishnagopal, Garrett E. Katz, Michelle Girvan, James A. Reggia
2019	J	`jnl`	Forecasting of Spatio-temporal Chaotic Dynamics with Recurrent Neural Networks: a comparative study of Reservoir Computing and Backpropagation Algorithms. CoRR Pantelis-Rafail Vlachas, Jaideep Pathak, Brian R. Hunt, Themistoklis P. Sapsis, Michelle Girvan, Edward Ott, Petros Koumoutsakos
2019	J	`jnl`	Separation of Chaotic Signals by Reservoir Computing. CoRR Sanjukta Krishnagopal, Michelle Girvan, Edward Ott, Brian R. Hunt
2018	J	`jnl`	Hybrid Forecasting of Chaotic Processes: Using Machine Learning in Conjunction with a Knowledge-Based Model. CoRR Jaideep Pathak, Alexander Wikner, Rebeckah Fussell, Sarthak Chandra, Brian R. Hunt, Michelle Girvan, Edward Ott
2018	J	`jnl`	Similarity Learning and Generalization with Limited Data: A Reservoir Computing Approach. Complex. Sanjukta Krishnagopal, Yiannis Aloimonos, Michelle Girvan
2016	J	`jnl`	The Myopia of Crowds: A Study of Collective Evaluation on Stack Exchange. CoRR Keith Burghardt, Emanuel F. Alsina, Michelle Girvan, William Rand, Kristina Lerman
2015	J	`jnl`	Complexity-Regularized Regression for Serially-Correlated Residuals with Applications to Stock Market Data. Entropy David Darmon, Michelle Girvan
2015	J	`jnl`	Finding New Order in Biological Functions from the Network Structure of Gene Annotations. PLoS Comput. Biol. Kimberly Glass, Michelle Girvan
2015	B	`conf`	Forecasting High Tide: Predicting Times of Elevated Activity in Online Social Media. ASONAM Jimpei Harada, David Darmon, Michelle Girvan, William Rand
2014	J	`jnl`	Competing Opinions and Stubborness: Connecting Models to Data. CoRR Keith Burghardt, William Rand, Michelle Girvan
2014	J	`jnl`	The Impact of Imperfect Information on Network Attack. CoRR Andrew Melchionna, Jesus Caloca, Shane Squires, Thomas M. Antonsen Jr., Edward Ott, Michelle Girvan
2013	—	`conf`	Predictability of User Behavior in Social Media: Bottom-Up v. Top-Down Modeling. SocialCom David Darmon, Jared Sylvester, Michelle Girvan, William Rand
2013	J	`jnl`	Predictability of User Behavior in Social Media: Bottom-Up v. Top-Down Modeling. CoRR David Darmon, Jared Sylvester, Michelle Girvan, William Rand
2013	J	`jnl`	Robustness of Network Measures to Link Errors. CoRR John Platig, Edward Ott, Michelle Girvan
2013	J	`jnl`	Spatially embedded growing small-world networks. CoRR Ari Zitin, Alex Gorowora, Shane Squires, Mark Herrera, Thomas M. Antonsen Jr., Michelle Girvan, Edward Ott
2013	—	`conf`	Topological properties of chromosome conformation graphs reflect spatial proximities within chromatin. BCB Hao Wang, Geet Duggal, Rob Patro, Michelle Girvan, Sridhar Hannenhalli, Carl Kingsford