ProSelfLC-AT
noisy labels; missing labels; semi-supervised learning; entropy; uncertainty; robustness and generalisation. (by XinshaoAmosWang)
ProSelfLC
noisy labels; missing labels; semi-supervised learning; entropy; uncertainty; robustness and generalisation. [Moved to: https://github.com/XinshaoAmosWang/ProSelfLC-AT] (by XinshaoAmosWang)
| ProSelfLC-AT | ProSelfLC | |
|---|---|---|
| 4 | 1 | |
| 58 | 50 | |
| - | - | |
| 1.8 | 10.0 | |
| almost 2 years ago | almost 2 years ago | |
| HTML | HTML | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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.
ProSelfLC-AT
Posts with mentions or reviews of ProSelfLC-AT.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-11-25.
-
[R] Robust Learning: the past and present. The DNN has strong fitting capability, but we find ...
Found relevant code at https://github.com/XinshaoAmosWang/ProSelfLC-AT + all code implementations here
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[R] ProSelfLC: Progressive Self Label Correction Towards A Low-Temperature Entropy State
Code for https://arxiv.org/abs/2207.00118 found: https://github.com/XinshaoAmosWang/ProSelfLC-AT
- [P] Easy to install, use, extend, run experiments and sink results: PyTorch Implementation for ProSelfLC-CVPR 2021
- [R] CVPR 2021-Progressive Self Label Correction (ProSelfLC) for Training Robust Deep Neural Networks
ProSelfLC
Posts with mentions or reviews of ProSelfLC.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-08-10.
-
[Research] Deep Critical Learning (i.e., Deep Robustness) In The Era of Big Data
Code for https://arxiv.org/abs/2005.03788 found: https://github.com/XinshaoAmosWang/ProSelfLC
What are some alternatives?
When comparing ProSelfLC-AT and ProSelfLC you can also consider the following projects:
imodels - Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
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
Improving-Mean-Absolute-Error-against-CCE - Mean Absolute Error Does Not Treat Examples Equally and Gradient Magnitude’s Variance Matters
romodel - Modeling robust optimization problems in Pyomo