William H. Guss
Publications by Year
Research Areas
Reinforcement Learning in Robotics, Robot Manipulation and Learning, Neural Networks and Applications, Machine Learning and Data Classification, Adversarial Robustness in Machine Learning
Most-Cited Works
- → Evaluating Large Language Models Trained on Code(2021)1,403 cited
- → MineRL: A Large-Scale Dataset of Minecraft Demonstrations(2019)93 cited
- → On Characterizing the Capacity of Neural Networks using Algebraic Topology(2018)60 cited
- → The MineRL 2019 Competition on Sample Efficient Reinforcement Learning using Human Priors(2019)47 cited
- → The MineRL 2020 Competition on Sample Efficient Reinforcement Learning using Human Priors(2021)14 cited
- → Multi-task curriculum learning in a complex, visual, hard-exploration domain: Minecraft(2021)9 cited
- → Deep Function Machines: Generalized Neural Networks for Topological Layer Expression(2016)8 cited
- → Retrospective Analysis of the 2019 MineRL Competition on Sample Efficient Reinforcement Learning(2020)8 cited
- → Measuring Sample Efficiency and Generalization in Reinforcement Learning Benchmarks: NeurIPS 2020 Procgen Benchmark(2021)6 cited