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larsandClaude Sonnet 5 af2ee7c7ce Add gumbel router configs sweeping learnable-knob combinations
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Extends the 10-expert EnergyRouter + physical-conditioning benchmark
config with the new opt-in gumbel combine weights, isolating the
learn_centers/learn_temperature axis: none, centers only, and
centers+temperature.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
 2026-07-30 16:40:02 +02:00
larsandClaude Sonnet 5 db0f12be58 Add configs for router energy (embedding/physical) and WGAN baseline runs 
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
 2026-07-27 15:53:04 +02:00
larsandClaude Sonnet 4.6 9277d79dff Implement Phase 1: full data pipeline, model, training, and config support 
- Data pipeline: loader (parquet→numpy), transforms (log, local-frame
  Rodrigues rotation, Normalizer), StepsDataset with event-ID-based split
- Model: SinusoidalEmbedding, ConditionEncoder, ResBlock, DenoisingMLP
- Schedule: cosine DDPM and conditional flow matching loss (Lipman 2022)
- Samplers: flow (Euler ODE), DDPM ancestral, DDIM deterministic
- Training loop: AdamW + cosine LR, grad clipping, best-val checkpoint
- Validation: per-dimension marginal summary (normalised space)
- CLI: TOML config support with CLI-overrides; hyperparam-encoded output
  directory; config.toml with git hash saved into each run's checkpoint dir
- 21 unit tests covering transforms, network, flow/DDPM losses, dataset splits

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
 2026-06-17 10:48:03 +02:00