Data-Efficient-Reinforcement-Learning-with-Probabilistic-Model-Predictive-Control
Robo-Semantic-Segmentation
Data-Efficient-Reinforcement-Learning-with-Probabilistic-Model-Predictive-Control | Robo-Semantic-Segmentation | |
---|---|---|
2 | 1 | |
114 | 0 | |
- | - | |
4.5 | 0.0 | |
12 months ago | over 3 years ago | |
Python | Python | |
MIT License | MIT License |
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.
Data-Efficient-Reinforcement-Learning-with-Probabilistic-Model-Predictive-Control
- MPC with Gaussian processes for data-efficient reinforcement learning
-
[OC] Visualizations of the learning of probabilistic model predictive control for reinforcement learning
Link to repositery: https://github.com/SimonRennotte/Data-Efficient-Reinforcement-Learning-with-Probabilistic-Model-Predictive-Control
Robo-Semantic-Segmentation
-
Where do I even start? Image segmentation.
Hi, you can look at this https://github.com/The-ML-Hero/Robo-Semantic-Segmentation/ which is my GitHub repo. This repo is all about segmentation specifically semantic segmentation, I have a couple of questions where did you get the dataset? and do you have the dataset ready?. But before you use the code be sure to understand the workings of semantic image segmentation architectures. The repo is implemented in Pytorch which is in the python language.
What are some alternatives?
stable-baselines3 - PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
ros-semantic-segmentation-pytorch - Pytorch implementation of Semantic Segmentation in ROS on MIT ADE20K dataset based on semantic-segmentation-pytorch by CSAIL
Machine-Learning-Collection - A resource for learning about Machine learning & Deep Learning
torch-metrics - Metrics for model evaluation in pytorch
ProSelfLC-AT - noisy labels; missing labels; semi-supervised learning; entropy; uncertainty; robustness and generalisation.
PyTorch-VAE - A Collection of Variational Autoencoders (VAE) in PyTorch.
ALAE - [CVPR2020] Adversarial Latent Autoencoders
ludwig - Low-code framework for building custom LLMs, neural networks, and other AI models
d2l-en - Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
torch-points3d - Pytorch framework for doing deep learning on point clouds.
Implicit-Internal-Video-Inpainting - [ICCV 2021]: IIVI: Internal Video Inpainting by Implicit Long-range Propagation
TTNet-Real-time-Analysis-System-for-Table-Tennis-Pytorch - Unofficial implementation of "TTNet: Real-time temporal and spatial video analysis of table tennis" (CVPR 2020)