0.2.4

What's changed

• Opt-in time rescaling for datasets with large inter-event times (#55): set data_specs.rescale_time: true to divide all event times by the mean training inter-event time (or set an explicit data_specs.time_scale). Time predictions and RMSE are reported in original units; the resolved scale is persisted in the model config. Default behavior is unchanged when the flag is off.
• Fix multi-step generation padding bug (#13): predict_multi_step_since_last_event now respects batch_non_pad_mask — previously, every sequence shorter than the batch max conditioned on pad events and was compared against pad labels.
• IntensityFree now supports thinning and multi-step generation (#13): new compute_intensities_at_sample_times implements the closed-form hazard of the log-normal mixture, lambda_k(t) = f(t)/S(t) * p(k|history).
• New Colab deep-dive notebooks (linked from the README): log-space statistics in IntensityFree (#84) and multi-step generation / intensity-free thinning (#13), plus examples/verify_multistep_generation.py.
• New regression tests: tests/test_multi_step_generation.py and time-rescaling config tests.