Hierarchical biomarker thresholding: a model-agnostic framework for stability
Fuente:
arXiv
Saved in:
| Main Author: | Debeaupuis, O. |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
On the calibration of survival models with competing risks
by: Alberge, Julie, et al.
Published: (2026)
by: Alberge, Julie, et al.
Published: (2026)
Testing for LLM response differences: the case of a composite null consisting of semantically irrelevant query perturbations
by: Acharyya, Aranyak, et al.
Published: (2025)
by: Acharyya, Aranyak, et al.
Published: (2025)
A fine-grained look at causal effects in causal spaces
by: Park, Junhyung, et al.
Published: (2025)
by: Park, Junhyung, et al.
Published: (2025)
A General Framework on Conditions for Constraint-based Causal Learning
by: Teh, Kai Z., et al.
Published: (2024)
by: Teh, Kai Z., et al.
Published: (2024)
A note on incorrect inferences in non-binary qualitative probabilistic networks
by: Carter, Jack Storror
Published: (2022)
by: Carter, Jack Storror
Published: (2022)
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)
Inference on summaries of a model-agnostic longitudinal variable importance trajectory with application to suicide prevention
by: Williamson, Brian D., et al.
Published: (2023)
by: Williamson, Brian D., et al.
Published: (2023)
Federated Causal Inference from Multi-Site Observational Data via Propensity Score Aggregation
by: Khellaf, Rémi, et al.
Published: (2025)
by: Khellaf, Rémi, et al.
Published: (2025)
A Tutorial on Asymptotic Properties for Biostatisticians with Applications to COVID-19 Data
by: Cui, Elvis Han
Published: (2022)
by: Cui, Elvis Han
Published: (2022)
Class conditional conformal prediction for multiple inputs by p-value aggregation
by: Fermanian, Jean-Baptiste, et al.
Published: (2025)
by: Fermanian, Jean-Baptiste, et al.
Published: (2025)
Causal Sufficiency and Necessity Improves Chain-of-Thought Reasoning
by: Yu, Xiangning, et al.
Published: (2025)
by: Yu, Xiangning, et al.
Published: (2025)
Le Cam Distortion: A Decision-Theoretic Framework for Robust Transfer Learning
by: Akdemir, Deniz
Published: (2025)
by: Akdemir, Deniz
Published: (2025)
Statistical Inference for Optimal Transport Maps: Recent Advances and Perspectives
by: Balakrishnan, Sivaraman, et al.
Published: (2025)
by: Balakrishnan, Sivaraman, et al.
Published: (2025)
Bias-Aware Conformal Prediction for Metric-Based Imaging Pipelines
by: Cheung, Matt Y., et al.
Published: (2024)
by: Cheung, Matt Y., et al.
Published: (2024)
Revisiting Incremental Stochastic Majorization-Minimization Algorithms with Applications to Mixture of Experts
by: Tran, TrungKhang, et al.
Published: (2026)
by: Tran, TrungKhang, et al.
Published: (2026)
Pessimism in the Face of Confounders: Provably Efficient Offline Reinforcement Learning in Partially Observable Markov Decision Processes
by: Lu, Miao, et al.
Published: (2022)
by: Lu, Miao, et al.
Published: (2022)
Interaction Testing in Variation Analysis
by: Plecko, Drago
Published: (2024)
by: Plecko, Drago
Published: (2024)
CITE: Anytime-Valid Statistical Inference in LLM Self-Consistency
by: Ota, Hirofumi, et al.
Published: (2026)
by: Ota, Hirofumi, et al.
Published: (2026)
Label Noise Robustness of Conformal Prediction
by: Einbinder, Bat-Sheva, et al.
Published: (2022)
by: Einbinder, Bat-Sheva, et al.
Published: (2022)
A Likelihood Based Approach to Distribution Regression Using Conditional Deep Generative Models
by: Kumar, Shivam, et al.
Published: (2024)
by: Kumar, Shivam, et al.
Published: (2024)
Foundations of Structural Causal Models with Latent Selection
by: Chen, Leihao, et al.
Published: (2024)
by: Chen, Leihao, et al.
Published: (2024)
Evaluating LLMs When They Do Not Know the Answer: Statistical Evaluation of Mathematical Reasoning via Comparative Signals
by: Dong, Zihan, et al.
Published: (2026)
by: Dong, Zihan, et al.
Published: (2026)
Conformal Risk Control
by: Angelopoulos, Anastasios N., et al.
Published: (2022)
by: Angelopoulos, Anastasios N., et al.
Published: (2022)
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)
Dimension-agnostic inference using cross U-statistics
by: Kim, Ilmun, et al.
Published: (2020)
by: Kim, Ilmun, et al.
Published: (2020)
A Bayesian framework with adaptive elastic nets for the inference of Gaussian graphical models
by: Sogan, Roland B., et al.
Published: (2026)
by: Sogan, Roland B., et al.
Published: (2026)
Model-agnostic information transfer and fusion for classification with label noise
by: Guojun, Zhu, et al.
Published: (2026)
by: Guojun, Zhu, et al.
Published: (2026)
Forecasting time series with constraints
by: Doumèche, Nathan, et al.
Published: (2025)
by: Doumèche, Nathan, et al.
Published: (2025)
It's Hard to Be Normal: The Impact of Noise on Structure-agnostic Estimation
by: Jin, Jikai, et al.
Published: (2025)
by: Jin, Jikai, et al.
Published: (2025)
A network-constrain Weibull AFT model for biomarkers discovery
by: Angelini, Claudia, et al.
Published: (2024)
by: Angelini, Claudia, et al.
Published: (2024)
Conditional partial exchangeability: a probabilistic framework for multi-view clustering
by: Franzolini, Beatrice, et al.
Published: (2023)
by: Franzolini, Beatrice, et al.
Published: (2023)
A framework for statistical modelling of the extremes of longitudinal data, applied to elite swimming
by: Spearing, Jess, et al.
Published: (2023)
by: Spearing, Jess, et al.
Published: (2023)
Unifying design-based and model-based sampling theory -- some suggestions to clear the cobwebs
by: O'Neill, Ben
Published: (2024)
by: O'Neill, Ben
Published: (2024)
From Data-Driven to Purpose-Driven Artificial Intelligence: Systems Thinking for Data-Analytic Automation of Patient Care
by: Anadria, Daniel, et al.
Published: (2025)
by: Anadria, Daniel, et al.
Published: (2025)
Differentially private inference framework of Riemannian manifold data
by: Jiang, Yangdi, et al.
Published: (2026)
by: Jiang, Yangdi, et al.
Published: (2026)
Structure-agnostic Optimality of Doubly Robust Learning for Treatment Effect Estimation
by: Jin, Jikai, et al.
Published: (2024)
by: Jin, Jikai, et al.
Published: (2024)
Exploratory Hierarchical Factor Analysis with an Application to Psychological Measurement
by: Qiao, Jiawei, et al.
Published: (2025)
by: Qiao, Jiawei, et al.
Published: (2025)
On the Hierarchical Bayes justification of Empirical Bayes Confidence Intervals
by: Sen, Aditi, et al.
Published: (2025)
by: Sen, Aditi, et al.
Published: (2025)
Asymmetric Space-Time Covariance Functions via Hierarchical Mixtures
by: Ma, Pulong
Published: (2025)
by: Ma, Pulong
Published: (2025)
An autocovariance-based learning framework for high-dimensional functional time series
by: Chang, Jinyuan, et al.
Published: (2020)
by: Chang, Jinyuan, et al.
Published: (2020)
Similar Items
-
On the calibration of survival models with competing risks
by: Alberge, Julie, et al.
Published: (2026) -
Testing for LLM response differences: the case of a composite null consisting of semantically irrelevant query perturbations
by: Acharyya, Aranyak, et al.
Published: (2025) -
A fine-grained look at causal effects in causal spaces
by: Park, Junhyung, et al.
Published: (2025) -
A General Framework on Conditions for Constraint-based Causal Learning
by: Teh, Kai Z., et al.
Published: (2024) -
A note on incorrect inferences in non-binary qualitative probabilistic networks
by: Carter, Jack Storror
Published: (2022)