| Multi-objective goal-directed optimization of de novo stable organic radicals for aqueous redox flow batteries SS SV, JN Law, CE Tripp, D Duplyakin, E Skordilis, D Biagioni, RS Paton, ... Nature Machine Intelligence 4 (8), 720-730, 2022 | 39 | 2022 |
| Transferable reinforcement learning for smart homes X Zhang, X Jin, C Tripp, DJ Biagioni, P Graf, H Jiang Proceedings of the 1st international workshop on reinforcement learning for …, 2020 | 22 | 2020 |
| A modular and transferable reinforcement learning framework for the fleet rebalancing problem E Skordilis, Y Hou, C Tripp, M Moniot, P Graf, D Biagioni IEEE Transactions on Intelligent Transportation Systems 23 (8), 11903-11916, 2021 | 10 | 2021 |
| A simplified, efficient approach to hybrid wind and solar plant site optimization C Tripp, D Guittet, J King, A Barker Wind Energy Science 7 (2), 697-713, 2022 | 8 | 2022 |
| FRC: a high-performance concurrent parallel deferred reference counter for C++ C Tripp, D Hyde, B Grossman-Ponemon Acm Sigplan Notices 53 (5), 14-28, 2018 | 8 | 2018 |
| Short-term wind forecasting using statistical models with a fully observable wind flow J Perr-Sauer, C Tripp, M Optis, J King Journal of Physics: Conference Series 1452 (1), 012083, 2020 | 7 | 2020 |
| Stochastic agent-based model for predicting turbine-scale raptor movements during updraft-subsidized directional flights R Sandhu, C Tripp, E Quon, R Thedin, M Lawson, D Brandes, CJ Farmer, ... Ecological Modelling 466, 109876, 2022 | 6 | 2022 |
| Hybrid optimization and performance platform (HOPP) CE Tripp, D Guittet, A Barker, J King, B Hamilton National Renewable Energy Laboratory (NREL), Golden, CO (United States), 2019 | 6 | 2019 |
| Finding similar images based on extracting keys from images C Tripp, J Li US Patent 9,384,519, 2016 | 5 | 2016 |
| Approximate Kalman filter Q-learning for continuous state-space MDPs C Tripp, RD Shachter arXiv preprint arXiv:1309.6868, 2013 | 4 | 2013 |
| Virtual engineering (ve)(vebio) E Young, J Stickel, H Sitaraman, A Glaws, J Lischeske National Renewable Energy Laboratory (NREL), Golden, CO (United States), 2022 | 3* | 2022 |
| A cyber-physical system for freeway ramp meter signal control using deep reinforcement learning in a connected environment Y Hou, X Zhang, P Graf, C Tripp, D Biagioni 2021 IEEE International Intelligent Transportation Systems Conference (ITSC …, 2021 | 3 | 2021 |
| Backtracking for more efficient large scale dynamic programming C Tripp, R Shachter 2012 11th International Conference on Machine Learning and Applications 1 …, 2012 | 3 | 2012 |
| graphenv: a Python library for reinforcement learning on graph search spaces D Biagioni, CE Tripp, S Clark, D Duplyakin, J Law, PCS John Journal of Open Source Software 7 (77), 4621, 2022 | 2 | 2022 |
| Green AI: Insights Into Deep Learning's Looming Energy Efficiency Crisis C Tripp, E Bensen, L Hayne, J Perr-Sauer, M Lunacek National Renewable Energy Lab.(NREL), Golden, CO (United States), 2022 | 1 | 2022 |
| An Empirical Deep Dive into Deep Learning's Driving Dynamics CE Tripp, J Perr-Sauer, L Hayne, M Lunacek arXiv preprint arXiv:2207.12547, 2022 | 1 | 2022 |
| Ssrs (stochastic soaring raptor simulator) R Sandhu, C Tripp, E Quon, R Thedin, L Williams, P Doubrawa, C Draxl, ... National Renewable Energy Lab.(NREL), Golden, CO (United States), 2021 | 1 | 2021 |
| A simplified, efficient approach to hybrid wind and solar plant site optimization C Tripp, D Guittet, J King, A Barker Wind Energy Science Discussions 2021, 1-22, 2021 | 1 | 2021 |
| rlmolecule: A library for general-purpose material and molecular optimization using AlphaZero-style reinforcement learning D Biagioni, E Skordilis, C Tripp, D Duplyakin, P St John National Renewable Energy Laboratory (NREL), Golden, CO (United States), 2020 | 1 | 2020 |
| A three-dimensional model of terrain-induced updrafts for movement ecology studies R Thedin, D Brandes, E Quon, R Sandhu, C Tripp Movement Ecology 12 (1), 25, 2024 | | 2024 |
David BiagioniProofpointVerified email at proofpoint.com
