| Bellman: A Toolbox for Model-Based Reinforcement Learning in TensorFlow | Mar 26, 2021 | Model-based Reinforcement Learningreinforcement-learning | CodeCode Available | 1 | 5 |
| Learning safety in model-based Reinforcement Learning using MPC and Gaussian Processes | Nov 3, 2022 | Gaussian ProcessesModel-based Reinforcement Learning | CodeCode Available | 1 | 5 |
| DyNODE: Neural Ordinary Differential Equations for Dynamics Modeling in Continuous Control | Sep 9, 2020 | continuous-controlContinuous Control | CodeCode Available | 1 | 5 |
| Learning to Adapt in Dynamic, Real-World Environments Through Meta-Reinforcement Learning | Mar 30, 2018 | continuous-controlContinuous Control | CodeCode Available | 1 | 5 |
| Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning | Jun 15, 2020 | Model-based Reinforcement Learningreinforcement-learning | CodeCode Available | 1 | 5 |
| Dream and Search to Control: Latent Space Planning for Continuous Control | Oct 19, 2020 | continuous-controlContinuous Control | CodeCode Available | 1 | 5 |
| Dynamics-Aware Unsupervised Discovery of Skills | Jul 2, 2019 | Model-based Reinforcement LearningReinforcement Learning | CodeCode Available | 1 | 5 |
| Diminishing Return of Value Expansion Methods in Model-Based Reinforcement Learning | Mar 7, 2023 | continuous-controlContinuous Control | CodeCode Available | 1 | 5 |
| DISCOVER: Deep identification of symbolically concise open-form PDEs via enhanced reinforcement-learning | Oct 4, 2022 | Deep Reinforcement LearningForm | CodeCode Available | 1 | 5 |
| Dream to Drive with Predictive Individual World Model | Jan 28, 2025 | Autonomous Drivingmodel | CodeCode Available | 1 | 5 |
