mlsanityData to 7 Oct 2026

Interacting Contour Stochastic Gradient Langevin Dynamics

arXiv 2202.09867 ↗First posted 20 Feb 2022stat.ML cs.LGcited by 9

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Abstract (arXiv)

We propose an interacting contour stochastic gradient Langevin dynamics (ICSGLD) sampler, an embarrassingly parallel multiple-chain contour stochastic gradient Langevin dynamics (CSGLD) sampler with efficient interactions. We show that ICSGLD can be theoretically more efficient than a single-chain CSGLD with an equivalent computational budget. We also present a novel random-field function, which facilitates the estimation of self-adapting parameters in big data and obtains free mode explorations. Empirically, we compare the proposed algorithm with popular benchmark methods for posterior sampling. The numerical results show a great potential of ICSGLD for large-scale uncertainty estimation tasks.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 28 of its 67 references that are in the map. First posted on arXiv 20 Feb 2022.

Builds on

28 of 67 references.

References · 28

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16 more
  1. 2015Non-asymptotic convergence analysis for the Unadjusted Langevin Algorithmcited by 195
  2. 2015Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural Networkscited by 121
  3. 2017Global Convergence of Langevin Dynamics Based Algorithms for Nonconvex Optimizationcited by 96
  4. 2017A Hitting Time Analysis of Stochastic Gradient Langevin Dynamicscited by 70
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  7. 2018Global Non-convex Optimization with Discretized Diffusionscited by 44
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  9. 2019Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyondcited by 33
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  11. 2020A Contour Stochastic Gradient Langevin Dynamics Algorithm for Simulations of Multi-modal Distributionscited by 26
  12. 2018Stochastic Particle-Optimization Sampling and the Non-Asymptotic Convergence Theorycited by 20
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  16. 2016Interacting Particle Markov Chain Monte Carlocited by 6

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Cited by year

Citing papers per year: 2022: 1; 2023: 2; 2024: 3; 2025: 3.

9 papers.

  1. 2024Reflected Schr"odinger Bridge for Constrained Generative Modelingcited by 12
  2. 2024Accelerating Approximate Thompson Sampling with Underdamped Langevin Monte Carlocited by 10
  3. 2022Non-reversible Parallel Tempering for Deep Posterior Approximationcited by 7
  4. 2024Constrained Exploration via Reflected Replica Exchange Stochastic Gradient Langevin Dynamicscited by 7
  5. 2023Non-Log-Concave and Nonsmooth Sampling via Langevin Monte Carlo Algorithmscited by 4
  6. 2025Morephy-Net: An Evolutionary Multi-objective Optimization for Replica-Exchange-based Physics-informed Neural Operator Learning Networkscited by 3
  7. 2023The surrogate Gibbs-posterior of a corrected stochastic MALA: Towards uncertainty quantification for neural networkscited by 0
  8. 2025Efficient Weighted Sampling via Score-based Generative Modelscited by 0
  9. 2025Flatness-Aware Stochastic Gradient Langevin Dynamicscited by 0