Data-Efficient-Reinforcement-Learning-with-Probabilistic-Model-Predictive-Control VS deep-kernel-transfer

Compare Data-Efficient-Reinforcement-Learning-with-Probabilistic-Model-Predictive-Control vs deep-kernel-transfer and see what are their differences.

Data-Efficient-Reinforcement-Learning-with-Probabilistic-Model-Predictive-Control

Unofficial Implementation of the paper "Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control", applied to gym environments (by SimonRennotte)
reinforcement-learning Pytorch pytorch-implementation gpytorch gaussian-processes model-predictive-control model-based-reinforcement-learning Paper control-animation uncertainty
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deep-kernel-transfer

Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020) (by BayesWatch)
gaussian-processes few-shot-learning bayesian-methods Deep Learning deep-kernel-learning one-shot-learning kernel-methods Classification Regression gpytorch Kernel shot-learning uncertainty-quantification uncertainty Paper meta-learning kernels
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Data-Efficient-Reinforcement-Learning-with-Probabilistic-Model-Predictive-Control deep-kernel-transfer
2 1
114 190
- 1.6%
4.5 10.0
12 months ago over 2 years ago
Python Python
MIT License -
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Data-Efficient-Reinforcement-Learning-with-Probabilistic-Model-Predictive-Control

Posts with mentions or reviews of Data-Efficient-Reinforcement-Learning-with-Probabilistic-Model-Predictive-Control. We have used some of these posts to build our list of alternatives and similar projects.

deep-kernel-transfer

Posts with mentions or reviews of deep-kernel-transfer. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing Data-Efficient-Reinforcement-Learning-with-Probabilistic-Model-Predictive-Control and deep-kernel-transfer you can also consider the following projects:

stable-baselines3 - PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

FSL-Mate - FSL-Mate: A collection of resources for few-shot learning (FSL).

Machine-Learning-Collection - A resource for learning about Machine learning & Deep Learning

ipme - An interactive visualization tool that transforms probabilistic programming models into an "Interactive Probabilistic Models Explorer".

ProSelfLC-AT - noisy labels; missing labels; semi-supervised learning; entropy; uncertainty; robustness and generalisation.

fortuna - A Library for Uncertainty Quantification.

Robo-Semantic-Segmentation - Just a simple semantic segmentation library that I developed to speed up the image segmentation pipeline

rcps - Official codebase for "Distribution-Free, Risk-Controlling Prediction Sets"

ALAE - [CVPR2020] Adversarial Latent Autoencoders

MLBox - MLBox is a powerful Automated Machine Learning python library.

Data-Efficient-Reinforcement-Learning-with-Probabilistic-Model-Predictive-Control vs stable-baselines3 deep-kernel-transfer vs FSL-Mate Data-Efficient-Reinforcement-Learning-with-Probabilistic-Model-Predictive-Control vs Machine-Learning-Collection deep-kernel-transfer vs ipme Data-Efficient-Reinforcement-Learning-with-Probabilistic-Model-Predictive-Control vs ProSelfLC-AT deep-kernel-transfer vs fortuna Data-Efficient-Reinforcement-Learning-with-Probabilistic-Model-Predictive-Control vs Robo-Semantic-Segmentation deep-kernel-transfer vs rcps Data-Efficient-Reinforcement-Learning-with-Probabilistic-Model-Predictive-Control vs ALAE deep-kernel-transfer vs MLBox