Egemen Kolemen

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 15

Top Topics

Reservoir Computing

Dynamical Systems

Recurrent Networks

Reinforcement Learning

Top Venues

Publications

Sara Dubbioso, Azarakhsh Jalalvand, Josiah Wai, Gianmaria De Tommasi, Egemen Kolemen
Model-free stabilization via Extremum Seeking using a cost neural estimator. Expert Syst. Appl. 258 (2024)
Azarakhsh Jalalvand, Max Curie, SangKyeun Kim, Peter Steiner, Jaemin Seo, Qiming Hu, Andrew Oakleigh Nelson, Egemen Kolemen
Diag2Diag: Multimodal super-resolution diagnostics for physics discovery with application to fusion. CoRR (2024)
Ian Char, Youngseog Chung, Joseph Abbate, Egemen Kolemen, Jeff G. Schneider
Full Shot Predictions for the DIII-D Tokamak via Deep Recurrent Networks. CoRR (2024)
Rory Conlin, Patrick Kim, Daniel W. Dudt, Dario Panici, Egemen Kolemen
Stellarator Optimization with Constraints. CoRR (2024)
Jaemin Seo, SangKyeun Kim, Azarakhsh Jalalvand, Rory Conlin, Andrew Rothstein, Joseph Abbate, Keith Erickson, Josiah Wai, Ricardo Shousha, Egemen Kolemen
Avoiding fusion plasma tearing instability with deep reinforcement learning. Nat. 626 (8000) (2024)
Jaemin Seo, Rory Conlin, Andrew Rothstein, SangKyeun Kim, Joseph Abbate, Azarakhsh Jalalvand, Egemen Kolemen
Multimodal Prediction of Tearing Instabilities in a Tokamak. IJCNN (2023)
Alvin V. Garcia, Azarakhsh Jalalvand, Peter Steiner, Andrew Rothstein, Michael Van Zeeland, William W. Heidbrink, Egemen Kolemen
Alfvén eigenmode detection using Long-Short Term Memory Networks and CO2 Interferometer data on the DIII-D National Fusion Facility. IJCNN (2023)
Ian Char, Joseph Abbate, Laszlo Bardoczi, Mark D. Boyer, Youngseog Chung, Rory Conlin, Keith Erickson, Viraj Mehta, Nathan Richner, Egemen Kolemen, Jeff G. Schneider
Offline Model-Based Reinforcement Learning for Tokamak Control. L4DC (2023)
Azarakhsh Jalalvand, Joseph Abbate, Rory Conlin, Geert Verdoolaege, Egemen Kolemen
Real-Time and Adaptive Reservoir Computing With Application to Profile Prediction in Fusion Plasma. IEEE Trans. Neural Networks Learn. Syst. 33 (6) (2022)
Rory Conlin, Daniel W. Dudt, Dario Panici, Egemen Kolemen
The DESC Stellarator Code Suite Part II: Perturbation and continuation methods. CoRR (2022)
Rory Conlin, Keith Erickson, Joseph Abbate, Egemen Kolemen
Keras2c: A library for converting Keras neural networks to real-time compatible C. Eng. Appl. Artif. Intell. 100 (2021)
Viraj Mehta, Ian Char, Willie Neiswanger, Youngseog Chung, Andrew Oakleigh Nelson, Mark D. Boyer, Egemen Kolemen, Jeff G. Schneider
Neural Dynamical Systems: Balancing Structure and Flexibility in Physical Prediction. CDC (2021)
Youngseog Chung, Ian Char, Willie Neiswanger, Kirthevasan Kandasamy, Andrew Oakleigh Nelson, Mark D. Boyer, Egemen Kolemen, Jeff Schneider
Offline Contextual Bayesian Optimization for Nuclear Fusion. CoRR (2020)
Viraj Mehta, Ian Char, Willie Neiswanger, Youngseog Chung, Andrew Oakleigh Nelson, Mark D. Boyer, Egemen Kolemen, Jeff Schneider
Neural Dynamical Systems: Balancing Structure and Flexibility in Physical Prediction. CoRR (2020)
Ian Char, Youngseog Chung, Willie Neiswanger, Kirthevasan Kandasamy, Oak Nelson, Mark D. Boyer, Egemen Kolemen
Offline Contextual Bayesian Optimization. NeurIPS (2019)