Comments (2)
hanruisong00
commented on May 23, 2024
1
Thank you, it is my pleasure, my email is [email protected], if you have any questions or I can help, you can contact me
from torch-uncertainty.
o-laurent
commented on May 23, 2024
Hi, that's why we love open source!
Thank you very much for this very relevant remark. After a discussion with @alafage, we are confident that you are right, and this may be a difference with Deep Ensembles that we had not anticipated. The first experiment I ran (R18-C10) shows an improved performance for Packed-Ensembles, but this remains to be thoroughly verified. I'll start a branch for this, which raises some technical questions (there may be a more user-friendly way to do this than multiply the lr). Would you like to be a co-author of the first commit with @alafage and me? To do so, I'd just need your email (potentially the "noreply" one from GitHub if you don't want to share your personal address).
from torch-uncertainty.
Related Issues (20)
- :bug: Some tests pass despite code errors HOT 1
- :bug: Enable torch cpu enforcement in poetry config HOT 1
- Add Deep Evidential Regression HOT 1
- Add support for CIFAR-N
- :sparkles: Add support for Tiny-ImageNet-C HOT 8
- :sparkles: Add an MCDropout Baseline
- :sparkles: Enable custom distributions for probabilistic regression
- :sparkles: Add support for depth regression datasets and models
- :shirt: Improve the calibration plots
- :shirt: Fix plot size in the docs
- :wrench: Fix codecov upload in forked PRs HOT 3
- :bug: Calibration plot error
- :bug: issue concerning the interaction of MC-Dropout and the other methods HOT 2
- :sparkles: Add the Adaptive Calibration Error (ECE with adaptive bins)
- :sparkles: Add support for Monocular depth estimation
- :bug: The Grouping Loss test does not always pass
- :sparkles: Add Superpixel-Mix augmentation for Segmentation models
- :sparkles: Implement LPBNN
- :bug: Reduce the memory usage of the segmentation metrics
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from torch-uncertainty.