dlmacedo/robust-deep-learning

A project to train your model from scratch or fine-tune a pretrained model using the losses provided in this library to improve out-of-distribution detection and uncertainty estimation performances. Calibrate your model to produce enhanced uncertainty estimations. Detect out-of-distribution data using the defined score type and threshold.

Language: Python - Size: 4.16 MB - Last synced at: about 2 months ago - Pushed at: over 2 years ago - Stars: 17 - Forks: 3

dlmacedo/distinction-maximization-loss

A project to improve out-of-distribution detection (open set recognition) and uncertainty estimation by changing a few lines of code in your project! Perform efficient inferences (i.e., do not increase inference time) without repetitive model training, hyperparameter tuning, or collecting additional data.

Language: Python - Size: 2.45 MB - Last synced at: 4 months ago - Pushed at: almost 3 years ago - Stars: 45 - Forks: 5

dlmacedo/starter-academic

Language: Jupyter Notebook - Size: 153 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 6 - Forks: 3

dlmacedo/SVM-CNN

A feature extractor based on Python 3, Tensorflow, and Scikit-learn created to improve the SVM accuracy to classify the MNIST dataset fast and with more accuracy.

Language: Python - Size: 1.43 MB - Last synced at: almost 2 years ago - Pushed at: over 2 years ago - Stars: 64 - Forks: 44

dlmacedo/entropic-out-of-distribution-detection

A project to add scalable state-of-the-art out-of-distribution detection (open set recognition) support by changing two lines of code! Perform efficient inferences (i.e., do not increase inference time) and detection without classification accuracy drop, hyperparameter tuning, or collecting additional data.

Language: Python - Size: 7.71 MB - Last synced at: over 2 years ago - Pushed at: almost 3 years ago - Stars: 51 - Forks: 8