:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Author:	Befekadu, Getachew K.
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2601.22441
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Embedding generalization within the learning dynamics: An approach based-on sample path large deviation theory
by: Befekadu, Getachew K.
Published: (2024)

On characterizing optimal learning trajectories in a class of learning problems
by: Befekadu, Getachew K
Published: (2025)

A decision-theoretic model for a principal-agent collaborative learning problem
by: Befekadu, Getachew K
Published: (2024)

A brief note on learning problem with global perspectives
by: Befekadu, Getachew K.
Published: (2026)

A naive aggregation algorithm for improving generalization in a class of learning problems
by: Befekadu, Getachew K
Published: (2024)

A successive approximation method in functional spaces for hierarchical optimal control problems and its application to learning
by: Befekadu, Getachew K.
Published: (2024)

On improving generalization in a class of learning problems with the method of small parameters for weakly-controlled optimal gradient systems
by: Befekadu, Getachew K.
Published: (2024)

A new perspective on the learning dynamics for a class of learning problems via averaged gradient systems coupled with diffusion-transmutation processes
by: Befekadu, Getachew K.
Published: (2024)

Further extensions on the successive approximation method for hierarchical optimal control problems and its application to learning
by: Befekadu, Getachew K.
Published: (2024)

Simulation-based Bayesian inference under model misspecification
by: Kelly, Ryan P., et al.
Published: (2025)

ForwardFlow: Simulation only statistical inference using deep learning
by: Böhringer, Stefan
Published: (2026)

Another look at statistical inference with machine learning-imputed data
by: Gronsbell, Jessica, et al.
Published: (2024)

Explainability as statistical inference
by: Senetaire, Hugo Henri Joseph, et al.
Published: (2022)

Hybrid summary statistics: neural weak lensing inference beyond the power spectrum
by: Makinen, T. Lucas, et al.
Published: (2024)

Unrolled denoising networks provably learn optimal Bayesian inference
by: Karan, Aayush, et al.
Published: (2024)

Simulation-based inference of yeast centromeres
by: Touron, Eloïse, et al.
Published: (2025)

Resampling methods for private statistical inference
by: Chadha, Karan, et al.
Published: (2024)

Reparameterization invariance in approximate Bayesian inference
by: Roy, Hrittik, et al.
Published: (2024)

FNOPE: Simulation-based inference on function spaces with Fourier Neural Operators
by: Moss, Guy, et al.
Published: (2025)

Black-box Bayesian inference for economic agent-based models
by: Dyer, Joel, et al.
Published: (2022)

On statistical learning of graphs
by: Cipriani, Vittorio, et al.
Published: (2025)

Transfer learning for multifidelity simulation-based inference in cosmology
by: Saoulis, Alex A., et al.
Published: (2025)

Dimension-agnostic inference using cross U-statistics
by: Kim, Ilmun, et al.
Published: (2020)

Simulation-based inference via telescoping ratio estimation for trawl processes
by: Leonte, Dan, et al.
Published: (2025)

An efficient likelihood-free Bayesian inference method based on sequential neural posterior estimation
by: Xiong, Yifei, et al.
Published: (2023)

Fast post-process Bayesian inference with Variational Sparse Bayesian Quadrature
by: Li, Chengkun, et al.
Published: (2023)

Stein transport for Bayesian inference
by: Nüsken, Nikolas
Published: (2024)

Efficient nonparametric statistical inference on population feature importance using Shapley values
by: Williamson, Brian D., et al.
Published: (2020)

BlackJAX: Composable Bayesian inference in JAX
by: Cabezas, Alberto, et al.
Published: (2024)

Approximate Bayesian inference for cumulative probit regression models
by: Aliverti, Emanuele
Published: (2025)

When can weak latent factors be statistically inferred?
by: Fan, Jianqing, et al.
Published: (2024)

Universal priors: solving empirical Bayes via Bayesian inference and pretraining
by: Cannella, Nick, et al.
Published: (2026)

Tensor cumulants for statistical inference on invariant distributions
by: Kunisky, Dmitriy, et al.
Published: (2024)

Variational Bayesian inference for CP tensor completion with side information
by: Budzinskiy, Stanislav, et al.
Published: (2022)

mlr3summary: Concise and interpretable summaries for machine learning models
by: Dandl, Susanne, et al.
Published: (2024)

Simulation-based Bayesian Inference from Privacy Protected Data
by: Xiong, Yifei, et al.
Published: (2023)

Representation learning with CGAN for casual inference
by: Weng, Zhaotian, et al.
Published: (2024)

Active learning for data-driven reduced models of parametric differential systems with Bayesian operator inference
by: McQuarrie, Shane A., et al.
Published: (2025)

Monte Carlo inference for semiparametric Bayesian regression
by: Kowal, Daniel R., et al.
Published: (2023)

Simulation-based inference for stochastic nonlinear mixed-effects models with applications in systems biology
by: Häggström, Henrik, et al.
Published: (2025)