software
Selected research software and reproducibility code.
FlowBench
PyTorch benchmark for reproducible evaluation of diffusion and flow-matching models under Gaussian and heavy-tailed generative settings.
Artifacts: benchmark description available on request
Keywords: diffusion models, flow matching, heavy-tailed distributions, reproducible benchmarks
Metis
AutoML toolbox for model selection, ensembling, and predictive-performance optimization.
Artifacts: description available on request
Keywords: AutoML, model selection, ensembling, predictive optimization
optimal_bootstrap
Code for high-dimensional analysis of bootstrap ensemble classifiers. This project accompanies the AISTATS work on bootstrap methods for LSSVM ensembles, random matrix theory, and practical rules for selecting ensemble hyperparameters.
Keywords: bootstrap ensembles, random matrix theory, high-dimensional statistics
Bandpy
Gym-compatible Python package for benchmarking single- and multi-agent bandit algorithms across synthetic and real-data environments.
Artifacts: code
Keywords: multi-agent bandits, benchmarking, Gym environments, reproducible experiments
HemoLearn
Python package for estimating the haemodynamic response function from resting-state or task fMRI BOLD signals using blind deconvolution.
Artifacts: code
Keywords: fMRI, haemodynamic response function, blind deconvolution, inverse problems
Carpet
Research code for solving 1D total-variation regularized optimization problems, including classical solvers and learnable unrolled optimization algorithms.
Keywords: unrolled optimization, total variation, inverse problems, sparse regularization