Mlearning.ai

FEBRUARY 15, 2023

Deep learning models with multilayer processing architecture are now outperforming shallow or standard classification models in terms of performance [5]. Deep ensemble learning models utilise the benefits of both deep learning and ensemble learning to produce a model with improved generalisation performance.

Cross Validation 52

Cross Validation Decision Trees Algorithm Natural Language Processing 52

ML @ CMU

NOVEMBER 7, 2024

For the Risk Modeling component, we designed a novel interpretable deep learning tabular model extending TabNet. To validate the proposed system, we simulate different scenarios in which the RELand system could be deployed in mine clearance operations using real data from Colombia. Validation results in Colombia.

Clustering 153

Clustering Cross Validation Machine Learning Machine Learning 153

Heartbeat

JUNE 14, 2023

On mixup training: Improved calibration and predictive uncertainty for deep neural networks.” Measuring Calibration in Deep Learning. Eighth JPL Airborne Geoscience Workshop. 4] Szegedy, Christian, et al. Rethinking the inception architecture for computer vision. 5] Müller, Rafael, Simon Kornblith, and Geoffrey E.

Deep Learning 59

Deep Learning Deep Learning Support Vector Machines Machine Learning 59