fractal_rl
Code for CORL 2020 paper: Explicitly Encouraging Low Fractional Dimensional Trajectories Via Reinforcement Learning. (by sgillen)
pillbox
Contains implementation of AdVIL, AdRIL, and DAeQuIL algorithms from the ICML '21 Paper Of Moments and Matching. (by gkswamy98)
| fractal_rl | pillbox | |
|---|---|---|
| 2 | 2 | |
| 7 | 21 | |
| - | - | |
| 0.0 | 0.0 | |
| about 3 years ago | about 2 years ago | |
| Jupyter Notebook | Jupyter Notebook | |
| - | - |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
fractal_rl
Posts with mentions or reviews of fractal_rl.
We have used some of these posts to build our list of alternatives
and similar projects.
pillbox
Posts with mentions or reviews of pillbox.
We have used some of these posts to build our list of alternatives
and similar projects.
What are some alternatives?
When comparing fractal_rl and pillbox you can also consider the following projects:
pywonderland - A tour in the wonderland of math with python.
AvatarGAN - Generate Cartoon Images using Generative Adversarial Network
brax - Massively parallel rigidbody physics simulation on accelerator hardware.
daydreamer - DayDreamer: World Models for Physical Robot Learning
nn - 🧑🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠