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Glass chemistry measurements for investigating small-sample materials classification.

Surface-vehicle sensor streams for investigating motion prediction and sensor consistency.

Genetic programming for symbolic regression and related transformations.

Hierarchical density-based clustering with support for variable-density structure and noise labels.

Forecast reconciliation and evaluation for hierarchical and grouped time series.

Artificial sampled curves for testing classification of local geometric structure under noise.

Radio-survey candidate descriptors for inspecting imbalanced pulsar detection.

Code-generation evaluation repository for examining functional correctness and pass-at-k estimation on programming tasks.

Simulated robot trajectories for preparing a reproducible motion-prediction benchmark.

Resampling methods and pipeline tools for learning from imbalanced classes.

Evaluation framework for composing tasks, model interactions, scoring and inspectable logs.

Radar-return descriptors for testing classification and calibration under limited sample sizes.