DiffusionControl / README.md
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---
license: other
tags:
- diffusion
- control
- controller-synthesis
---
# DiffusionControl checkpoints
Trained models for the DiffusionControl project (conditional diffusion models that generate
certified feedback controllers). Code, protocols and results live in the GitHub repo
`matCercola18/matte_server` under `DiffusionControl/`, branch `icml-experiments`; each family has
a research doc in `DiffusionControl/docs/`.
Files keep their repo paths (`models/...`), so code that loads `models/<name>.pth` works after
`huggingface_hub.snapshot_download`. Only final checkpoints are included (no `Last_*`, no
intermediate step checkpoints).
| family | files | doc |
|---|---|---|
| Furuta (QUBE-Servo 2), headline 1D U-Net generator | `models/v4/unet_a*_s96000.pth`, `unet_s_s40000.pth`, `unet_sxd_s40000.pth` | `furuta_generated_trajectory_v4.md` |
| Furuta regression twins and MLP ablations | `models/v4/reg_*`, `models/v4/mlp_*` | same |
| Furuta earlier trajectory models (v1-v3, clip-bug fix) | `Best_furuta_traj_cond_*` | `furuta_generated_trajectory*.md` |
| Furuta energy-shaping models (superseded) | `Best_furuta_cond`, `_full_cond`, `_handoff_cond` | `diffusion_complete_nonlinear_controller.md` |
| Pendulum | `Best_pendulum_*` (multi-solution `multi_*`, physics-informed `pg_*`/`abl_dl_*`, ablations `abl_*`) | `pendulum_multi_solution.md`, `physics_informed_generation.md`, `ablations.md`, `ood_shift.md` |
| SISO Lur'e | `Best_nonlinear_cond_popov_*`, `siso_pg_c*`, `costcond_siso`, `cert_perfspan_L`, `regressor_siso` | RESULTS.md, `physics_informed_generation.md` |
| MIMO 2x2 | `Best_mimo_cond_2x2*` | RESULTS.md |
| CVAE baselines | `Best_cvae_*` | `ablations.md` |
| Witsenhausen | `*witsenhausen_cond*` | `witsenhausen.md` |
Note: `Best_nonlinear_cond_popov_L_sector/_closedloop/_distill` are documented negative results.