Precup, Doina

The multimodal brain tumor image segmentation benchmark (BRATS)

Menze, B. H., Jakab, A., Bauer, S., Kalpathy-Cramer, J., Farahani, K., Kirby, J., Burren, Y., Porz, N., Slotboom, J., Wiest, R., et al. (2015) · IEEE Transactions on Medical Imaging

Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques

Cited by 6,781

Between MDPs and semi-MDPs: A framework for temporal abstraction in reinforcement learning

Sutton, R. S., Precup, D., & Singh, S. (1999) · Artificial Intelligence

Reinforcement Learning in RoboticsAI-based Problem Solving and Planning

Cited by 3,119

Deep Reinforcement Learning That Matters

Henderson, P., Islam, R., Bachman, P., Pineau, J., Precup, D., & Meger, D. (2018) · Proceedings of the AAAI Conference on Artificial Intelligence

Reinforcement Learning in RoboticsScientific Computing and Data Management

Cited by 1,685

Exploring uncertainty measures in deep networks for Multiple sclerosis lesion detection and segmentation

Nair, T., Precup, D., Arnold, D. L., & Arbel, T. (2020) · Medical Image Analysis

Medical Image Segmentation TechniquesAdvanced Neural Network Applications

Cited by 451

Reward is enough

Silver, D., Singh, S., Precup, D., & Sutton, R. S. (2021) · Artificial Intelligence

Reinforcement Learning in RoboticsPsychiatry, Mental Health, Neuroscience

Cited by 445

Towards Continual Reinforcement Learning: A Review and Perspectives

Khetarpal, K., Riemer, M., Rish, I., & Precup, D. (2020) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 227

Towards Continual Reinforcement Learning: A Review and Perspectives

Khetarpal, K., Riemer, M., Rish, I., & Precup, D. (2022) · Journal of Artificial Intelligence Research

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 224

Reproducibility of Benchmarked Deep Reinforcement Learning Tasks for Continuous Control

Islam, R., Henderson, P., Gomrokchi, M., & Precup, D. (2017) · arXiv

Reinforcement Learning in RoboticsAdaptive Dynamic Programming Control

Cited by 177

An information-theoretic approach to curiosity-driven reinforcement learning

Still, S., & Precup, D. (2012) · Theory in Biosciences

Reinforcement Learning in RoboticsAdvanced Bandit Algorithms Research

Cited by 165

A Survey of Exploration Methods in Reinforcement Learning

Amin, S., Gomrokchi, M., Satija, H., van Hoof, H., & Precup, D. (2021) · arXiv

Reinforcement Learning in RoboticsAdvanced Bandit Algorithms Research

Cited by 41

Learning Robust Options

Mankowitz, D., Mann, T., Bacon, P.-L., Precup, D., & Mannor, S. (2018) · Proceedings of the AAAI Conference on Artificial Intelligence

Reinforcement Learning in RoboticsAdaptive Dynamic Programming Control

Cited by 30

Training a First-Order Theorem Prover from Synthetic Data

Firoiu, V., Aygun, E., Anand, A., Ahmed, Z., Glorot, X., Orseau, L., Zhang, L., Precup, D., & Mourad, S. (2021) · arXiv

Logic, programming, and type systemsLogic, Reasoning, and Knowledge

Cited by 15

Interference and Generalization in Temporal Difference Learning

Bengio, E., Pineau, J., & Precup, D. (2020) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 14

Training Language Models to Self-Correct via Reinforcement Learning

Kumar, A., Zhuang, V., Agarwal, R., Su, Y., Co-Reyes, J. D., Singh, A., Baumli, K., Iqbal, S., Bishop, C., Roelofs, R., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 9

Agency Is Frame-Dependent

Abel, D., Barreto, A., Bowling, M., Dabney, W., Dong, S., Hansen, S., Harutyunyan, A., Khetarpal, K., Lyle, C., Pascanu, R., et al. (2025) · arXiv

Philosophy of Biology and Scientific ExplanationEmbodied and Extended Cognition

Cited by 0