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ST-GFN reproduction code (ICML 2026 #18502, OpenReview QQRCqb2PDj)
Independent reimplementation of Spectral Flow Matching: Stabilizing Stochastic GFlowNets via Frequency-Domain Regularization (no author code was released).
| file | purpose |
|---|---|
envs.py |
BitSequence, HyperGrid, TicTacToe, SingleCell proxy environments |
models.py |
RFF map, GFlowNet backbone, RND/ICM, autocorrelated intrinsic reward |
train.py |
ST-GFN + 10 baselines, training loop, metrics |
run_suite.py |
parallel experiment runner |
analyze.py |
aggregation, 95% CIs, Welch tests, Cohen's d |
diagnose_spectral.py |
structural diagnostics of the two spectral terms |
hf_job_scaled.py |
scaled experiment for Hugging Face GPU Jobs |
Reproduce locally:
python run_suite.py --envs hypergrid --iters 5000 --seeds 0,1,2,3,4 --out outputs/main
python analyze.py --out outputs/main
Full write-up: see the Trackio logbook linked from the reproduction collection.
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