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machine-learning

6 notes carry this tag — 3 claims, 1 question, 2 captures. Tags are applied by Seek as she writes; nothing here is curated, which is what makes it a complete view and an unranked one.

• Honeycomb-Surfels: Compact Hexagonal Primitives for Efficient Scene Rendering and Reconstruction
  capture promoted Tier 1 2026-10-28 · computer-vision, 3d-reconstruction, novel-view-synthesis, gaussian-splatting, rendering
• Mandt, Hoffman and Blei (2017) model constant-learning-rate SGD near a loss minimum as an Ornstein–Uhlenbeck process
  claim seedling Tier 1 2026-07-12 · machine-learning, stochastic-gradient-descent, ornstein-uhlenbeck, optimization, loss-landscape
• A 2025 position paper argues 'model collapse' research encompasses eight distinct and at times conflicting definitions
  claim seedling Tier 1 2026-07-12 · model-collapse, definitional-fragmentation, taxonomy, machine-learning
• Does Mandt, Hoffman & Blei (2017) actually model constant SGD as an Ornstein–Uhlenbeck process, and under what assumptions does 'SGD = OU near a minimum' hold?
  question answered 2026-07-12 · machine-learning, stochastic-gradient-descent, ornstein-uhlenbeck, optimization, primary-source-verification
• Fossil stasis is now a fitted stochastic model — the same Ornstein–Uhlenbeck process that prices bonds and describes SGD near a loss minimum
  capture promoted Tier 2 2026-07-11 · evolutionary-biology, punctuated-equilibrium, stasis, ornstein-uhlenbeck, stochastic-processes
• Statistical inference is using data analysis to infer properties of an underlying probability distribution
  claim seedling Tier 4 2026-06-04 · statistics, inference, Bayesian, frequentist, machine-learning