Cover Image

Properties and limitations of geometric tempering for gradient flow dynamics

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Crucinio, Francesca Romana, Pathiraja, Sahani
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Computation Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

An operator splitting analysis of Wasserstein--Fisher--Rao gradient flows
by: Crucinio, Francesca Romana, et al.
Published: (2025)

Sequential Monte Carlo approximations of Wasserstein--Fisher--Rao gradient flows
by: Crucinio, Francesca R., et al.
Published: (2025)

A note on the unique properties of the Kullback--Leibler divergence for sampling via gradient flows
by: Crucinio, Francesca Romana
Published: (2025)

Connections between sequential Bayesian inference and evolutionary dynamics
by: Pathiraja, Sahani, et al.
Published: (2024)

A mirror descent approach to maximum likelihood estimation in latent variable models
by: Crucinio, Francesca R.
Published: (2025)

Towards a turnkey approach to unbiased Monte Carlo estimation of smooth functions of expectations
by: Chopin, Nicolas, et al.
Published: (2024)

Interacting Particle Langevin Algorithm for Maximum Marginal Likelihood Estimation
by: Akyildiz, Ö. Deniz, et al.
Published: (2023)

FAStEN: An Efficient Adaptive Method for Feature Selection and Estimation in High-Dimensional Functional Regressions
by: Boschi, Tobia, et al.
Published: (2023)

Reliability analysis for non-deterministic limit-states using stochastic emulators
by: Pires, Anderson V., et al.
Published: (2024)

Conjugate gradient methods for high-dimensional GLMMs
by: Pandolfi, Andrea, et al.
Published: (2024)

Combining Wasserstein-1 and Wasserstein-2 proximals: robust manifold learning via well-posed generative flows
by: Gu, Hyemin, et al.
Published: (2024)

Binomial flows: Denoising and flow matching for discrete ordinal data
by: Shenfeld, Yair, et al.
Published: (2026)

Semi-Modular Inference: enhanced learning in multi-modular models by tempering the influence of components
by: Carmona, Chris U., et al.
Published: (2020)

Modelling non-stationary extremal dependence through a geometric approach
by: Murphy-Barltrop, C. J. R., et al.
Published: (2025)

A Doubly Robust Machine Learning Approach for Disentangling Treatment Effect Heterogeneity with Functional Outcomes
by: Salmaso, Filippo, et al.
Published: (2026)

Achieving Fairness with a Simple Ridge Penalty
by: Scutari, Marco, et al.
Published: (2021)

Modeling nonstationary spatial processes with normalizing flows
by: Nag, Pratik, et al.
Published: (2025)

Causal Estimation of Exposure Shifts with Neural Networks
by: Tec, Mauricio, et al.
Published: (2023)

Statistical ranking with dynamic covariates
by: Dong, Pinjun, et al.
Published: (2024)

Computing high-dimensional optimal transport by flow neural networks
by: Xu, Chen, et al.
Published: (2023)

A connection between Tempering and Entropic Mirror Descent
by: Chopin, Nicolas, et al.
Published: (2023)

On the role of surrogates in the efficient estimation of treatment effects with limited outcome data
by: Kallus, Nathan, et al.
Published: (2020)

Using Platt's scaling for calibration after undersampling -- limitations and how to address them
by: Phelps, Nathan, et al.
Published: (2024)

Fast Rerandomization for Balancing Covariates in Randomized Experiments: A Metropolis-Hastings Framework
by: Lu, Jiuyao, et al.
Published: (2026)

Semi-Supervised Mixture Models under the Concept of Missing at Radom with Margin Confidence and Aranda Ordaz Function
by: Liao, Jinyang, et al.
Published: (2026)

Conformalized Super Learner
by: Wu, Zhanli, et al.
Published: (2026)

Hypergraph Generation via Structured Stochastic Diffusion
by: Nemeth, Christopher
Published: (2026)

Safe, Scalable, and Accurate Bayes Posterior Sampling for Large-Data Generalized Linear Mixed Models
by: Baek, Youngsoo, et al.
Published: (2026)

High-dimensional reliability-based design optimization using stochastic emulators
by: Moustapha, M., et al.
Published: (2026)

Vertical Consensus Inference for High-Dimensional Random Partition
by: Nguyen, Khai, et al.
Published: (2026)

Anchored Variational Inference for Personalized Sequential Latent-State Models
by: Guo, Xingche
Published: (2026)

Preconditioned Robust Neural Posterior Estimation for Misspecified Simulators
by: Kelly, Ryan P., et al.
Published: (2026)

Non-Vacuous Certification of Transport MCMC via Oscillation-Controlled Normalizing Flows
by: Hu, Jun
Published: (2026)

Neural Generalized Mixed-Effects Models
by: Slavutsky, Yuli, et al.
Published: (2026)

Profile Graphical Models
by: Avalos-Pacheco, Alejandra, et al.
Published: (2026)

Proximal Projection for Doubly Sparse Regularized Models
by: He, Jia Wei, et al.
Published: (2026)

Robust Tensor Regression with Nonconvexity: Algorithmic and Statistical Theory
by: Song, Zihao, et al.
Published: (2026)

Leveraging heterogeneity for identifiability: Bayesian order-based learning of multiple DAGs
by: Chang, Hyunwoong, et al.
Published: (2026)

Learning Multi-type heterogeneous interacting particle systems
by: Lang, Quanjun, et al.
Published: (2026)

A Flexible Empirical Bayes Approach to Generalized Linear Models, with Applications to Sparse Logistic Regression
by: Xie, Dongyue, et al.
Published: (2026)