Cover Image

Uncertainty Quantification for Deep Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	van Leeuwen, Peter Jan, Chiu, J. Christine, Yang, C. Kevin
Format:	Preprint
Published:	2024
Subjects:	Machine Learning 62D99 G.3
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Unifying small area estimators based on area-level and unit-level models through calibration
by: Acero, William, et al.
Published: (2024)

A Robust Monotonic Single-Index Model for Skewed and Heavy-Tailed Data: A Deep Neural Network Approach Applied to Periodontal Studies
by: Liu, Qingyang, et al.
Published: (2025)

Multidimensional scaling of two-mode three-way asymmetric dissimilarities: finding archetypal profiles and clustering
by: Alcacer, Aleix, et al.
Published: (2025)

Non-asymptotic analysis of the performance of the penalized least trimmed squares in sparse models
by: Zuo, Yijun
Published: (2025)

Exchangeable Gaussian Processes for Staggered-Adoption Policy Evaluation
by: Gevorgyan, Hayk, et al.
Published: (2026)

Entropic optimal transport beyond product reference couplings: the Gaussian case on Euclidean space
by: Freulon, Paul, et al.
Published: (2025)

Examining the robustness of a model selection procedure in the binary latent block model through a language placement test data set
by: Brault, Vincent, et al.
Published: (2024)

An Imbalance-Robust Evaluation Framework for Extreme Risk Forecasts
by: Nikolopoulos, Sotirios D.
Published: (2025)

Partial Trace-Class Bayesian Neural Networks
by: Carter, Arran, et al.
Published: (2025)

SHIFT: Robust Double Machine Learning for Average Dose-Response Functions under Heavy-Tailed Contamination
by: Uehara, Eichi
Published: (2026)

Active sampling: A machine-learning-assisted framework for finite population inference with optimal subsamples
by: Imberg, Henrik, et al.
Published: (2022)

Clustering risk in Non-parametric Hidden Markov and I.I.D. Models
by: Gassiat, Elisabeth, et al.
Published: (2023)

A logical alarm for misaligned binary classifiers
by: Corrada-Emmanuel, Andrés, et al.
Published: (2024)

Emulating complex dynamical simulators with random Fourier features
by: Mohammadi, Hossein, et al.
Published: (2021)

Yet Another Representation of Binary Decision Trees: A Mathematical Demonstration
by: Zhang, Jinxiong
Published: (2021)

On some practical challenges of conformal prediction
by: Hong, Liang, et al.
Published: (2025)

Beyond Point Estimates: Distributional Uncertainty in Machine Learning Performance Evaluation
by: Lehmann, Christoph, et al.
Published: (2025)

Visual analysis of bivariate dependence between continuous random variables
by: Erdely, Arturo, et al.
Published: (2024)

Polynomial Chaos Surrogate Construction for Random Fields with Parametric Uncertainty
by: Mueller, Joy N., et al.
Published: (2023)

Living Synthetic Benchmarks: A Neutral and Cumulative Framework for Simulation Studies
by: Bartoš, František, et al.
Published: (2025)

Single-Dataset Meta-Analysis For Many-Analysts And Multiverse Studies
by: Bartoš, František, et al.
Published: (2025)

Evolving Voices Based on Temporal Poisson Factorisation
by: Vávra, Jan, et al.
Published: (2024)

Enhancing Visual Interpretability and Explainability in Functional Survival Trees and Forests
by: Loffredo, Giuseppe, et al.
Published: (2025)

Dimensionality-Aware Outlier Detection: Theoretical and Experimental Analysis
by: Anderberg, Alastair, et al.
Published: (2024)

Nonparametric f-Modeling for Empirical Bayes Inference with Unequal and Unknown Variances
by: Zhao, Zhigen, et al.
Published: (2026)

Distribution-Free Uncertainty Quantification for Continuous AI Agent Evaluation
by: Gao, Yuxuan, et al.
Published: (2026)

Proper Correlation Coefficients for Nominal Random Variables
by: Wermuth, Jan-Lukas
Published: (2025)

M-estimation under Two-Phase Multiwave Sampling with Applications to Prediction-Powered Inference
by: Kluger, Dan M., et al.
Published: (2026)

Deep learning with missing data
by: Ma, Tianyi, et al.
Published: (2025)

Transport map unadjusted Langevin algorithms: learning and discretizing perturbed samplers
by: Zhang, Benjamin J., et al.
Published: (2023)

Integrative Analysis and Imputation of Multiple Data Streams via Deep Gaussian Processes
by: Septiandri, Ali Akbar, et al.
Published: (2025)

Active Learning for Manifold Gaussian Process Regression
by: Cheng, Yuanxing, et al.
Published: (2025)

Measuring the originality of intellectual property assets based on machine learning outputs
by: Ragot, Sébastien
Published: (2020)

tidychangepoint: A Unified Framework for Analyzing Changepoint Detection in Univariate Time Series
by: Baumer, Benjamin S., et al.
Published: (2024)

Lower Bounds on Information Requirements for Causal Network Inference
by: Kang, Xiaohan, et al.
Published: (2021)

Maximum Likelihood Estimation of Optimal Receiver Operating Characteristic Curves from Likelihood Ratio Observations
by: Hajek, Bruce, et al.
Published: (2022)

Improving Variational Autoencoder Estimation from Incomplete Data with Mixture Variational Families
by: Simkus, Vaidotas, et al.
Published: (2024)

Global Minima by Penalized Full-dimensional Scaling
by: de Leeuw, Jan
Published: (2024)

Fundamental limits for weighted empirical approximations of tilted distributions
by: Iyer, Sarvesh Ravichandran, et al.
Published: (2025)

On the super-efficiency and robustness of the least squares of depth-trimmed regression estimator
by: Zuo, Yijun, et al.
Published: (2025)