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Name: Julian Lienen
Type: User
Bio: Lifelong student particularly interested in weakly-supervised learning, monocular depth estimation and AutoML.
Name: Julian Lienen
Type: User
Bio: Lifelong student particularly interested in weakly-supervised learning, monocular depth estimation and AutoML.
A Java library for infrastructural classes and basic algorithms in the area reasoning, search, and machine learning
A professionally curated list of awesome Conformal Prediction videos, tutorials, books, papers, PhD theses, articles and open-source libraries.
A curated list of resources for Learning with Noisy Labels
Supplementary material and code for "Conformal Credal Self-Supervised Learning" as published at COPA 2021.
Context-sensitive ranking and choice in Python with Tensorflow
Code for "Credal Self-Supervised Learning" as published at NeurIPS 2021.
Demo of a MNIST Classifier with TensorFlow
Repository providing access to commonly used depth estimation datasets
A simple method to perform semi-supervised learning with limited data.
Microsoft Flight Simulator (FSX) RESTful API and user interface to control user aircraft
Code for the paper "Instance Weighting through Data Imprecisiation" by Julian Lienen and Eyke Hüllermeier (International Journal of Approximate Reasoning [IJAR], 2021).
Supplementary material and code for "From Label Smoothing to Label Relaxation" as published at AAAI 2021.
Code for "Memorization-Dilation: Modeling Neural Collapse under Noise" as published at ICLR 2023.
Supplementary material and code for "Mitigating Label Noise through Data Ambiguation" as published at AAAI 2024.
Code of paper "A Geometric Analysis of Neural Collapse with Unconstrained Features"
Code for "Monocular Depth Estimation via Listwise Ranking using the Plackett-Luce Model" as published at CVPR 2021.
Robust Regression for Monocular Depth Estimation
Official Implementation of Robust Training under Label Noise by Over-parameterization
TensorFlow.js Tutorial
JAICore TSC documentation
[CVPR'22] Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.