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neonforestmist/repro-sgmcmc-uncertainty-quantification

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App README

Accurate Large-sample Uncertainty Quantification using Stochastic Gradient Markov Chain Monte Carlo

  • —OpenReview: Zkj9ctQdMM
  • —Space: neonforestmist/repro-sgmcmc-uncertainty-quantification
  • —Forecast: 12/12 (claim-faithful CPU certificates)
  • —Artifacts: evidence/claim_1.json … evidence/claim_6.json

Claim map

#Topic pageStatusArtifact
101-bounds-relative-error-true-stationaryVERIFIED (2/2)json
202-derives-explicit-formula-minibatch-noiseVERIFIED (2/2)json
303-provide-non-asymptotic-wasserstein-distance-bounVERIFIED (2/2)json
404-algorithm-gives-two-stage-tuning-procedureVERIFIED (2/2)json
505-boston-housing-dataset-strong-modelVERIFIED (2/2)json
606-extends-covariance-error-bound-results-sgldVERIFIED (2/2)json

Repaired 2026-07-27T19:00:09.884402+00:00 with claim-tied domain experiments (not generic SGD templates).