:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Lenzi, Amanda, Rue, Haavard
Format:	Preprint
Published:	2023
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2303.15041
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Low-rank variational Bayes correction to the Laplace method
by: van Niekerk, Janet, et al.
Published: (2021)

When the whole is greater than the sum of its parts: Scaling black-box inference to large data settings through divide-and-conquer
by: Hector, Emily C., et al.
Published: (2024)

Optimization on black-box function by parameter-shift rule
by: Hai, Vu Tuan
Published: (2025)

Demonstrating the power and flexibility of variational assumptions for amortized neural posterior estimation in environmental applications
by: Maceda, Elliot, et al.
Published: (2024)

Neural Likelihood Surfaces for Spatial Processes with Computationally Intensive or Intractable Likelihoods
by: Walchessen, Julia, et al.
Published: (2023)

A flexible Bayesian tool for CoDa mixed models: logistic-normal distribution with Dirichlet covariance
by: Martínez-Minaya, Joaquín, et al.
Published: (2023)

Towards more transferable adversarial attack in black-box manner
by: Lei, Chun Tong, et al.
Published: (2025)

Surrogate uncertainty estimation for your time series forecasting black-box: learn when to trust
by: Erlygin, Leonid, et al.
Published: (2023)

Wild refitting for black box prediction
by: Wainwright, Martin J.
Published: (2025)

The Bayesian Learning Rule
by: Khan, Mohammad Emtiyaz, et al.
Published: (2021)

Stabilizing black-box model selection with the inflated argmax
by: Adrian, Melissa, et al.
Published: (2024)

A Bayesian regression framework for circular models with INLA
by: Ye, Xiang, et al.
Published: (2026)

Scalable skewed Bayesian inference for latent Gaussian models
by: Dutta, Shourya, et al.
Published: (2025)

Leave-group-out cross-validation for latent Gaussian models
by: Liu, Zhedong, et al.
Published: (2022)

Joint control variate for faster black-box variational inference
by: Wang, Xi, et al.
Published: (2022)

Visualizing token importance for black-box language models
by: Rauba, Paulius, et al.
Published: (2025)

AED: An black-box NLP classifier model attacker
by: Liu, Yueyang, et al.
Published: (2021)

Personalizing black-box models for nonparametric regression with minimax optimality
by: Li, Sai, et al.
Published: (2026)

Opening the AI black box: program synthesis via mechanistic interpretability
by: Michaud, Eric J., et al.
Published: (2024)

From Black-box to Causal-box: Towards Building More Interpretable Models
by: Hwang, Inwoo, et al.
Published: (2025)

Concentration bounds on response-based vector embeddings of black-box generative models
by: Acharyya, Aranyak, et al.
Published: (2025)

Statistical inference on black-box generative models in the data kernel perspective space
by: Helm, Hayden, et al.
Published: (2024)

Domain Bridge: Generative model-based domain forensic for black-box models
by: Zhang, Jiyi, et al.
Published: (2024)

Towards consistency of rule-based explainer and black box model -- fusion of rule induction and XAI-based feature importance
by: Kozielski, Michał, et al.
Published: (2024)

Investigating Bayesian optimization for expensive-to-evaluate black box functions: Application in fluid dynamics
by: Diessner, Mike, et al.
Published: (2022)

Hoeffding decomposition of black-box models with dependent inputs
by: Idrissi, Marouane Il, et al.
Published: (2023)

Explore the vulnerability of black-box models via diffusion models
by: Shi, Jiacheng, et al.
Published: (2025)

Surrogate modeling for interpreting black-box LLMs in medical predictions
by: Han, Changho, et al.
Published: (2026)

Achieving interpretable machine learning by functional decomposition of black-box models into explainable predictor effects
by: Köhler, David, et al.
Published: (2024)

Inside the black box: Neural network-based real-time prediction of US recessions
by: Chung, Seulki
Published: (2023)

Batch and match: black-box variational inference with a score-based divergence
by: Cai, Diana, et al.
Published: (2024)

Modular addition without black-boxes: Compressing explanations of MLPs that compute numerical integration
by: Yip, Chun Hei, et al.
Published: (2024)

Low-rank surrogate modeling and stochastic zero-order optimization for training of neural networks with black-box layers
by: Chertkov, Andrei, et al.
Published: (2025)

Statistical inference for radial generalized Pareto distributions and return sets in geometric extremes
by: Papastathopoulos, Ioannis, et al.
Published: (2023)

Spatial Gaussian fields for complex areas with application to marine megafauna conservation
by: Heyl, Martina Le-Bert, et al.
Published: (2025)

A new avenue for Bayesian inference with INLA
by: van Niekerk, Janet, et al.
Published: (2022)

BONSAI: Structure-exploiting robust Bayesian optimization for networked black-box systems under uncertainty
by: Kudva, Akshay, et al.
Published: (2025)

Distributed Black-box Attack: Do Not Overestimate Black-box Attacks
by: Wu, Han, et al.
Published: (2022)

On Gradient-like Explanation under a Black-box Setting: When Black-box Explanations Become as Good as White-box
by: Cai, Yi, et al.
Published: (2023)

Efficient optimization of expensive black-box simulators via marginal means, with application to neutrino detector design
by: Kim, Hwanwoo, et al.
Published: (2025)