☆99Mar 24, 2023Updated 3 years ago
Alternatives and similar repositories for POPLIN
Users that are interested in POPLIN are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- ☆399Jul 18, 2019Updated 6 years ago
- Experiment code for "Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models"☆471Jul 6, 2023Updated 2 years ago
- Learning Action-Value Gradients in Model-based Policy Optimization☆32Sep 7, 2021Updated 4 years ago
- Algorithmic Framework for Model-based Deep Reinforcement Learning with Theoretical Guarantees☆93Sep 13, 2019Updated 6 years ago
- Code for reproducing experiments in Model-Based Active Exploration, ICML 2019☆81Jul 23, 2019Updated 6 years ago
- NordVPN Special Discount Offer • AdSave on top-rated NordVPN 1 or 2-year plans with secure browsing, privacy protection, and support for for all major platforms.
- Learning Off-Policy with Online Planning [CoRL 2021 Best Paper Finalist]☆42Aug 27, 2022Updated 3 years ago
- Code for the paper "When to Trust Your Model: Model-Based Policy Optimization"☆540Nov 22, 2022Updated 3 years ago
- The Differentiable Cross-Entropy Method☆125Aug 14, 2020Updated 5 years ago
- Learning to Adapt in Dynamic, Real-World Environment through Meta-Reinforcement Learning☆218Dec 27, 2022Updated 3 years ago
- An easy to understand implementation of the paper "Model-Based Reinforcement Learning for Atari"☆18Sep 27, 2019Updated 6 years ago
- ☆11Oct 14, 2019Updated 6 years ago
- Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model☆154Oct 26, 2020Updated 5 years ago
- Algorithmic Framework for Model-based Deep Reinforcement Learning with Theoretical Guarantees☆55Jul 26, 2019Updated 6 years ago
- Code for "Calibrated Model-Based Deep Reinforcement Learning", ICML 2019.☆54May 15, 2019Updated 6 years ago
- GPU virtual machines on DigitalOcean Gradient AI • AdGet to production fast with high-performance AMD and NVIDIA GPUs you can spin up in seconds. The definition of operational simplicity.
- Unofficial Pytorch code for "Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models"