mlsanityData to 14 Oct 2026

Adaptive Path Integral Diffusion: AdaPID

arXiv 2512.11858 ↗First posted 5 Dec 2025cs.LG cond-mat.stat-mech cs.AIcited by 1

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Abstract (arXiv)

Diffusion-based samplers -- Score Based Diffusions, Bridge Diffusions and Path Integral Diffusions -- match a target at terminal time, but the real leverage comes from choosing the schedule that governs the intermediate-time dynamics. We develop a path-wise schedule -- selection gramework for Harmonic PID with a time-varying stiffness, exploiting Piece-Wise-Constant(PWC) parametrizations and a simple hierarchical refinement. We introduce schedule-sensitive Quality-of-Sampling (QoS) diagnostics. Assuming a Gaussian-Mixture (GM) target, we retain closed-form Green functions' ration and numerically stable, Neural-Network free oracles for predicted-state maps and score. Experiments in 2D show that QoS driven PWC schedules consistently improve early-exit fidelity, tail accuracy, conditioning of the dynamics, and speciation (label-selection) timing at fixed integration budgets.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 26 of its 51 references that are in the map. First posted on arXiv 5 Dec 2025.

Builds on

26 of 51 references.

References · 26

  1. 2020Denoising Diffusion Probabilistic Modelscited by 21,076
  2. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 9,122
  3. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,058
  4. 2022Flow Matching for Generative Modelingcited by 5,702
  5. 2023Stochastic Interpolants: A Unifying Framework for Flows and Diffusionscited by 939
  6. 2021Diffusion Schr"odinger Bridge with Applications to Score-Based Generative Modelingcited by 602
  7. 2024Dynamical Regimes of Diffusion Modelscited by 142
  8. 2022Flow Annealed Importance Sampling Bootstrapcited by 127
  9. 2024Iterated Denoising Energy Matching for Sampling from Boltzmann Densitiescited by 116
  10. 2019Theoretical guarantees for sampling and inference in generative models with latent diffusionscited by 97
  11. 2023Error Bounds for Flow Matching Methodscited by 91
  12. 2021Diffusion Normalizing Flowcited by 77
14 more
  1. 2023Non-Denoising Forward-Time Diffusionscited by 77
  2. 2024Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Samplingcited by 56
  3. 2024Improved off-policy training of diffusion samplerscited by 48
  4. 2024Transferable Boltzmann Generatorscited by 46
  5. 2025No Trick, No Treat: Pursuits and Challenges Towards Simulation-free Training of Neural Samplerscited by 28
  6. 2023Towards Predicting Equilibrium Distributions for Molecular Systems with Deep Learningcited by 26
  7. 2015Adaptive importance sampling for control and inferencecited by 23
  8. 2025Lipschitz-Guided Design of Interpolation Schedules in Generative Modelscited by 17
  9. 2025Optimal Scheduling of Dynamic Transportcited by 13
  10. 2024Schr"odinger Bridge with Quadratic State Cost is Exactly Solvablecited by 12
  11. 2024Harmonic Path Integral Diffusioncited by 11
  12. 2023U-Turn Diffusioncited by 8
  13. 2025Distribution estimation via Flow Matching with Lipschitz guaranteescited by 6
  14. 2024Space-Time Diffusion Bridgecited by 3

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.

Similar, not cited

Close in wording, no citation either way

  1. 2026Diffusion Path Samplers via Sequential Monte Carlo
  2. 2024Self-Refining Diffusion Samplers: Enabling Parallelization via Parareal Iterations
  3. 2025Tortoise and Hare Guidance: Accelerating Diffusion Model Inference with Multirate Integration
  4. 2023A Unified Sampling Framework for Solver Searching of Diffusion Probabilistic Models
  5. 2026Adaptive Second-Order Solvers for Fast Stochastic Diffusion Sampling
  6. 2025Functional Adjoint Sampler: Scalable Sampling on Infinite Dimensional Spaces
  7. 2025Are First-Order Diffusion Samplers Really Slower? A Fast Forward-Value Approach
  8. 2023On Accelerating Diffusion-Based Sampling Process via Improved Integration Approximation