tpopordanoska

PhD student in Machine Learning at KU Leuven.

KU LeuvenLeuven, Belgium

Pinned Repositories

diffAURC
Differentiable AURC
Language:HTML1 1 00
calibration-object-detection
Codebase for "Beyond Classification: Definition and Density-based Estimation of Calibration in Object Detection", published at WACV 2024.
Language:Python6 3 10
calibration_and_bias
Codebase for "On the relationship between calibrated predictors and unbiased volume estimation" (MICCAI 2021).
Language:Python8 2 01
confidence-intervals
Official code repository for "Distribution-Independent Confidence Intervals for the Eigendecomposition of Covariance Matrices via the Eigenvalue-Eigenvector Identity" (ICML 2021 Workshop on Distribution-Free Uncertainty Quantification).
Language:Python5 4 10
ece-kde
Codebase for "A Consistent and Differentiable Lp Canonical Calibration Error Estimator", published at NeurIPS 2022.
Language:Python14 2 01
explanatory-guided-learning
Codebase for “Machine Guides, Human Supervises: Interactive Learning with Global Explanations”.
Language:Python4 3 01
in-the-name-of-deep-learning
Computer vision project: In the name of Deep Learning
Language:Jupyter Notebook1 0 00
influencair
Language:Jupyter Notebook0 0 00
proper-calibration-error
Codebase for "Consistent and Asymptotically Unbiased Estimation of Proper Calibration Errors", published at AISTATS 2024.
Language:Jupyter Notebook3 1 00
tpopordanoska.github.io
Personal website
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tpopordanoska/ece-kde
Codebase for "A Consistent and Differentiable Lp Canonical Calibration Error Estimator", published at NeurIPS 2022.
Language:Python14 2 01
tpopordanoska/calibration_and_bias
Codebase for "On the relationship between calibrated predictors and unbiased volume estimation" (MICCAI 2021).
Language:Python8 2 01
tpopordanoska/calibration-object-detection
Codebase for "Beyond Classification: Definition and Density-based Estimation of Calibration in Object Detection", published at WACV 2024.
Language:Python6 3 10
tpopordanoska/confidence-intervals
Official code repository for "Distribution-Independent Confidence Intervals for the Eigendecomposition of Covariance Matrices via the Eigenvalue-Eigenvector Identity" (ICML 2021 Workshop on Distribution-Free Uncertainty Quantification).
Language:Python5 4 10
tpopordanoska/explanatory-guided-learning
Codebase for “Machine Guides, Human Supervises: Interactive Learning with Global Explanations”.
Language:Python4 3 01
tpopordanoska/proper-calibration-error
Codebase for "Consistent and Asymptotically Unbiased Estimation of Proper Calibration Errors", published at AISTATS 2024.
Language:Jupyter Notebook3 1 00
tpopordanoska/in-the-name-of-deep-learning
Computer vision project: In the name of Deep Learning
Language:Jupyter Notebook1 0 00
tpopordanoska/influencair
Language:Jupyter Notebook0 0 00
tpopordanoska/tpopordanoska.github.io
Personal website
Language:HTML0 1 00