rpg_timelens
multiagent-particle-envs
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| rpg_timelens | multiagent-particle-envs | |
|---|---|---|
| 4 | 6 | |
| 587 | 2,200 | |
| 0.2% | 4.1% | |
| 1.3 | 0.0 | |
| 12 months ago | 21 days ago | |
| Python | Python | |
| - | MIT License |
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rpg_timelens
- [news] Make Slow Motion Videos With AI! TimeLens explained: a new model for video frame interpolation published at CVPR2021
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Make Slow Motion Videos With AI! TimeLens explained: a new model for video frame interpolation
Official code: https://github.com/uzh-rpg/rpg_timelens
- Pushed Skyrim's graphics so hard I could smell something burning
- Is There an AI I Can Actually Use to Sharpen / Improve the Framerate of Videos?
multiagent-particle-envs
- Why is Q-learning always presented in such a math-heavy fashion? I just spent an hour dissecting this formula with a student -- only to strongly suspect there is a typo. Are there any good Q-Learning tutorials out there that *explain* the math instead of dropping it from the sky?
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Ideal size of the visual observation
Hi, I am using the MPE (https://github.com/openai/multiagent-particle-envs) and I'm planning to use a visual observation. I was wondering, what size should it be? I assume that if it is too large and the agents are only a few, I am wasting lots of compute for nothing and also the noise becomes a lot. But how to find the best size? 60x60x3 for example?
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Why does MADDPG use action log prob for Q (Critic) instead of sampled action?
Code for https://arxiv.org/abs/1706.02275 found: https://github.com/openai/multiagent-particle-envs
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I get an incredibly long error simply for trying to install an older version of Numpy
git clone https://github.com/openai/multiagent-particle-envs cd multiagent-particle-envs/ python -m venv maddpg echo env/ >> .gitignore .\maddpg\Scripts\activate pip install gym==0.10.5 pip install numpy==1.14.5
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Not as impressive as the one natural simulator that I made with visual programming languages Aka the future but this is good try for someone learning programming
If you wanted to make it an RL env that others could train, it might be a nicer looking version of https://github.com/openai/multiagent-particle-envs
What are some alternatives?
gpt-2 - Code for the paper "Language Models are Unsupervised Multitask Learners"
maddpg - Code for the MADDPG algorithm from the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"
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ALAE - [CVPR2020] Adversarial Latent Autoencoders
jukebox - Code for the paper "Jukebox: A Generative Model for Music"
qlib - Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL.
transferlearning - Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
openshot-qt - OpenShot Video Editor is an award-winning free and open-source video editor for Linux, Mac, and Windows, and is dedicated to delivering high quality video editing and animation solutions to the world.
Paperless - Scan, index, and archive all of your paper documents