eirli VS PaddleHelix

Compare eirli vs PaddleHelix and see what are their differences.

eirli

An Empirical Investigation of Representation Learning for Imitation (EIRLI), NeurIPS'21 (by HumanCompatibleAI)
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eirli PaddleHelix
1 1
37 789
- 1.1%
2.8 5.4
about 1 year ago about 2 months ago
Python Python
- Apache License 2.0
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.

eirli

Posts with mentions or reviews of eirli. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-12-11.

PaddleHelix

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

What are some alternatives?

When comparing eirli and PaddleHelix you can also consider the following projects:

calibrated-backprojection-network - PyTorch Implementation of Unsupervised Depth Completion with Calibrated Backprojection Layers (ORAL, ICCV 2021)

transferlearning - Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

dino - PyTorch code for Vision Transformers training with the Self-Supervised learning method DINO

dipy - DIPY is the paragon 3D/4D+ imaging library in Python. Contains generic methods for spatial normalization, signal processing, machine learning, statistical analysis and visualization of medical images. Additionally, it contains specialized methods for computational anatomy including diffusion, perfusion and structural imaging.

pytorch-metric-learning - The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.

typedb-ml - TypeDB-ML is the Machine Learning integrations library for TypeDB

f-IRL - Inverse Reinforcement Learning via State Marginal Matching, CoRL 2020

DeBERTa - The implementation of DeBERTa

pytorch_sac_ae - PyTorch implementation of Soft Actor-Critic + Autoencoder(SAC+AE)

Unsupervised-Classification - SCAN: Learning to Classify Images without Labels, incl. SimCLR. [ECCV 2020]

DI-drive - Decision Intelligence Platform for Autonomous Driving simulation.