This repository provides the code used to create the results presented in "Global canopy height regression and uncertainty estimation from GEDI LIDAR waveforms with deep ensembles".

Code for the paper "Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep Learning under Distribution Shift"

Single-cell Consensus Clusters of Encoded Subspaces

Ensemble deep learning of embeddings for clustering multimodal single-cell omics data

HARNet: Towards On-Device Incremental Learning using Deep Ensembles on Constrained Devices for Human Activity Recognition

Reproduction code + artifacts for “When Do Deep Ensembles Improve Robustness to Spurious Correlations?” (TU Delft, 2026).

Code for the paper "Something for (almost) nothing: improving deep ensemble calibration using unlabeled data"

Official code for the TMLR 2025 paper: "On Joint Regularization and Calibration in Deep Ensembles"

Label-free confidence estimation for neural networks - benchmarking MSP, MC Dropout, EDL, and Deep Ensembles with a novel unsupervised uncertainty metric.

PINN framework for aerospace asset risk pricing: monotonic RUL prediction, deep ensemble uncertainty, Monte Carlo residual value, lease pricing, portfolio optimisation. Results: RUL 290±90 cycles, residual 0.19M , l e a s e r a t e 0.19M, lease rate 300k/month. Modular for real NGAFID/FAA data.

Brain Tumor Segmentation with Deep Learning and Deep Ensembles

Testbed to compare simple deep ensembles