Saved in:
| Main Author: | Akyildiz, Ömer Deniz |
|---|---|
| Format: | Preprint |
| Published: |
2022
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2201.00409 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Adaptively Optimised Adaptive Importance Samplers
by: Perello, Carlos A. C. C., et al.
Published: (2023)
by: Perello, Carlos A. C. C., et al.
Published: (2023)
Sampling by averaging: A multiscale approach to score estimation
by: Cordero-Encinar, Paula, et al.
Published: (2025)
by: Cordero-Encinar, Paula, et al.
Published: (2025)
Nonasymptotic analysis of Stochastic Gradient Hamiltonian Monte Carlo under local conditions for nonconvex optimization
by: Akyildiz, Ömer Deniz, et al.
Published: (2020)
by: Akyildiz, Ömer Deniz, et al.
Published: (2020)
A fast non-reversible sampler for Bayesian finite mixture models
by: Ascolani, Filippo, et al.
Published: (2025)
by: Ascolani, Filippo, et al.
Published: (2025)
Mixing times of data-augmentation Gibbs samplers for high-dimensional probit regression
by: Ascolani, Filippo, et al.
Published: (2025)
by: Ascolani, Filippo, et al.
Published: (2025)
TabMixNN: A Unified Deep Learning Framework for Structural Mixed Effects Modeling on Tabular Data
by: Akdemir, Deniz
Published: (2025)
by: Akdemir, Deniz
Published: (2025)
Scale-adaptive and robust intrinsic dimension estimation via optimal neighbourhood identification
by: Di Noia, Antonio, et al.
Published: (2024)
by: Di Noia, Antonio, et al.
Published: (2024)
Multi forests: Variable importance for multi-class outcomes
by: Hornung, Roman, et al.
Published: (2024)
by: Hornung, Roman, et al.
Published: (2024)
A Proximal Newton Adaptive Importance Sampler
by: Elvira, Víctor, et al.
Published: (2024)
by: Elvira, Víctor, et al.
Published: (2024)
Generative adversarial learning with optimal input dimension and its adaptive generator architecture
by: Tan, Zhiyao, et al.
Published: (2024)
by: Tan, Zhiyao, et al.
Published: (2024)
Gaussian entropic optimal transport: Schrödinger bridges and the Sinkhorn algorithm
by: Akyildiz, O. Deniz, et al.
Published: (2024)
by: Akyildiz, O. Deniz, et al.
Published: (2024)
Improving the stability of the covariance-controlled adaptive Langevin thermostat for large-scale Bayesian sampling
by: Wei, Jiani, et al.
Published: (2025)
by: Wei, Jiani, et al.
Published: (2025)
Gradient-based optimization for variational empirical Bayes multiple regression
by: Banerjee, Saikat, et al.
Published: (2024)
by: Banerjee, Saikat, et al.
Published: (2024)
High-dimensional reliability-based design optimization using stochastic emulators
by: Moustapha, M., et al.
Published: (2026)
by: Moustapha, M., et al.
Published: (2026)
Relaxed Gaussian process interpolation: a goal-oriented approach to Bayesian optimization
by: Petit, Sébastien, et al.
Published: (2022)
by: Petit, Sébastien, et al.
Published: (2022)
Likelihood-Preserving Embeddings for Statistical Inference
by: Akdemir, Deniz
Published: (2025)
by: Akdemir, Deniz
Published: (2025)
Efficient optimization of expensive black-box simulators via marginal means, with application to neutrino detector design
by: Kim, Hwanwoo, et al.
Published: (2025)
by: Kim, Hwanwoo, et al.
Published: (2025)
pared: Model selection using multi-objective optimization
by: Das, Priyam, et al.
Published: (2025)
by: Das, Priyam, et al.
Published: (2025)
Tail-adaptive Bayesian shrinkage
by: Lee, Se Yoon, et al.
Published: (2020)
by: Lee, Se Yoon, et al.
Published: (2020)
Machine learning to optimize precision in the analysis of randomized trials: A journey in pre-specified, yet data-adaptive learning
by: Balzer, Laura B., et al.
Published: (2025)
by: Balzer, Laura B., et al.
Published: (2025)
Approximately optimal domain adaptation with Fisher's Linear Discriminant
by: Helm, Hayden S., et al.
Published: (2023)
by: Helm, Hayden S., et al.
Published: (2023)
Two-Sided Nearest Neighbors: An adaptive and minimax optimal procedure for matrix completion
by: Sadhukhan, Tathagata, et al.
Published: (2024)
by: Sadhukhan, Tathagata, et al.
Published: (2024)
Perturbative adaptive importance sampling for Bayesian LOO cross-validation
by: Chang, Joshua C, et al.
Published: (2024)
by: Chang, Joshua C, et al.
Published: (2024)
Decorrelated feature importance from local sample weighting
by: Fröhlich, Benedikt, et al.
Published: (2025)
by: Fröhlich, Benedikt, et al.
Published: (2025)
On diffusion-based generative models and their error bounds: The log-concave case with full convergence estimates
by: Bruno, Stefano, et al.
Published: (2023)
by: Bruno, Stefano, et al.
Published: (2023)
Learning covariate importance for matching in policy-relevant observational research
by: Zhang, Hongzhe, et al.
Published: (2024)
by: Zhang, Hongzhe, et al.
Published: (2024)
Optimistic search: Change point estimation for large-scale data via adaptive logarithmic queries
by: Kovács, Solt, et al.
Published: (2020)
by: Kovács, Solt, et al.
Published: (2020)
Bayesian optimization for mixed variables using an adaptive dimension reduction process: applications to aircraft design
by: Saves, Paul, et al.
Published: (2025)
by: Saves, Paul, et al.
Published: (2025)
Minimax optimal adaptive structured transfer learning through semi-parametric domain-varying coefficient model
by: Chen, Hanxiao, et al.
Published: (2026)
by: Chen, Hanxiao, et al.
Published: (2026)
Efficient nonparametric statistical inference on population feature importance using Shapley values
by: Williamson, Brian D., et al.
Published: (2020)
by: Williamson, Brian D., et al.
Published: (2020)
Transductive conformal inference with adaptive scores
by: Gazin, Ulysse, et al.
Published: (2023)
by: Gazin, Ulysse, et al.
Published: (2023)
Le Cam Distortion: A Decision-Theoretic Framework for Robust Transfer Learning
by: Akdemir, Deniz
Published: (2025)
by: Akdemir, Deniz
Published: (2025)
Kinetic Interacting Particle Langevin Monte Carlo
by: Oliva, Paul Felix Valsecchi, et al.
Published: (2024)
by: Oliva, Paul Felix Valsecchi, et al.
Published: (2024)
A Gradient Flow Approach to Solving Inverse Problems with Latent Diffusion Models
by: Wang, Tim Y. J., et al.
Published: (2025)
by: Wang, Tim Y. J., et al.
Published: (2025)
Learning Latent Variable Models via Jarzynski-adjusted Langevin Algorithm
by: Cuin, James, et al.
Published: (2025)
by: Cuin, James, et al.
Published: (2025)
Momentum SVGD-EM for Accelerated Maximum Marginal Likelihood Estimation
by: Rozzio, Adam, et al.
Published: (2026)
by: Rozzio, Adam, et al.
Published: (2026)
Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization
by: Zhang, Dinghuai, et al.
Published: (2023)
by: Zhang, Dinghuai, et al.
Published: (2023)
Pareto optimal proxy metrics
by: Zito, Alessandro, et al.
Published: (2023)
by: Zito, Alessandro, et al.
Published: (2023)
Kernel-based retrieval models for hyperspectral image data optimized with Kernel Flows
by: Duma, Zina-Sabrina, et al.
Published: (2024)
by: Duma, Zina-Sabrina, et al.
Published: (2024)
A general framework for inference on algorithm-agnostic variable importance
by: Williamson, Brian D., et al.
Published: (2020)
by: Williamson, Brian D., et al.
Published: (2020)
Similar Items
-
Adaptively Optimised Adaptive Importance Samplers
by: Perello, Carlos A. C. C., et al.
Published: (2023) -
Sampling by averaging: A multiscale approach to score estimation
by: Cordero-Encinar, Paula, et al.
Published: (2025) -
Nonasymptotic analysis of Stochastic Gradient Hamiltonian Monte Carlo under local conditions for nonconvex optimization
by: Akyildiz, Ömer Deniz, et al.
Published: (2020) -
A fast non-reversible sampler for Bayesian finite mixture models
by: Ascolani, Filippo, et al.
Published: (2025) -
Mixing times of data-augmentation Gibbs samplers for high-dimensional probit regression
by: Ascolani, Filippo, et al.
Published: (2025)