Nicholay Topin

Orcid: 0009-0006-5376-2801

According to our database1, Nicholay Topin authored at least 23 papers between 2014 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Explainable Reinforcement Learning: A Survey and Comparative Review.
ACM Comput. Surv., July, 2024

2022
A Survey of Explainable Reinforcement Learning.
CoRR, 2022

MAVIPER: Learning Decision Tree Policies for Interpretable Multi-agent Reinforcement Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Use-Case-Grounded Simulations for Explanation Evaluation.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
The MineRL BASALT Competition on Learning from Human Feedback.
CoRR, 2021

Towards robust and domain agnostic reinforcement learning competitions.
CoRR, 2021

The MineRL 2020 Competition on Sample Efficient Reinforcement Learning using Human Priors.
CoRR, 2021


Iterative Bounding MDPs: Learning Interpretable Policies via Non-Interpretable Methods.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Guaranteeing Reproducibility in Deep Learning Competitions.
CoRR, 2020


2019
Conservative Q-Improvement: Reinforcement Learning for an Interpretable Decision-Tree Policy.
CoRR, 2019

The MineRL Competition on Sample Efficient Reinforcement Learning using Human Priors.
CoRR, 2019

Retrospective Analysis of the 2019 MineRL Competition on Sample Efficient Reinforcement Learning.
Proceedings of the NeurIPS 2019 Competition and Demonstration Track, 2019

Online Planning for Autonomous Underwater Vehicles Performing Information Gathering Tasks in Large Subsea Environments.
Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019

MineRL: A Large-Scale Dataset of Minecraft Demonstrations.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Generation of Policy-Level Explanations for Reinforcement Learning.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2017
Super-Convergence: Very Fast Training of Residual Networks Using Large Learning Rates.
CoRR, 2017

Exploring loss function topology with cyclical learning rates.
CoRR, 2017

2016
Deep Convolutional Neural Network Design Patterns.
CoRR, 2016

Feature Selection in Environments with Limited Voluntary Information Sharing.
Proceedings of the IEEE International Conference on Data Mining Workshops, 2016

2015
Portable Option Discovery for Automated Learning Transfer in Object-Oriented Markov Decision Processes.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

2014
Discovering Subgoals in Complex Domains.
Proceedings of the 2014 AAAI Fall Symposia, Arlington, Virginia, USA, November 13-15, 2014, 2014


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