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Conor Igoe
Title
Cited by
Cited by
Year
How useful are gradients for ood detection really?
C Igoe, Y Chung, I Char, J Schneider
arXiv preprint arXiv:2205.10439, 2022
132022
Multi-agent active search: A reinforcement learning approach
C Igoe, R Ghods, J Schneider
IEEE Robotics and Automation Letters 7 (2), 754-761, 2021
112021
Hierarchical Bayesian framework for bus dwell time prediction
IK Isukapati, C Igoe, E Bronstein, V Parimi, SF Smith
IEEE Transactions on Intelligent Transportation Systems 22 (5), 3068-3077, 2020
112020
Multi-Alpha Soft Actor-Critic: Overcoming Stochastic Biases in Maximum Entropy Reinforcement Learning
C Igoe, S Pande, S Venkatraman, J Schneider
2023 IEEE International Conference on Robotics and Automation (ICRA), 7162-7168, 2023
22023
Multi-armed bandits with delayed and aggregated rewards
J Tyo, O Neopane, J Byrd, C Gupta, C Igoe, ...
DEVCOM Army Res. Lab., White Oak, MD, USA, Tech. Rep. ARL-TR-8754, 2019
22019
Integrating transit signal priority with adaptive signal control in a connected vehicle environment: Phase 1 Final Report
SF Smith, I Isukapati, E Bronstein, C Igoe
Carnegie-Mellon University, 2018
22018
Weighted tallying bandits: overcoming intractability via repeated exposure optimality
D Malik, C Igoe, Y Li, A Singh
International Conference on Machine Learning, 23590-23609, 2023
2023
Integrating Transit Signal Priority With Adaptive Signal Control in a Connected Vehicle Environment
SF Smith, I Isukapati, E Bronstein, C Igoe
2018
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Articles 1–8