Simplifying debiased inference via automatic differentiation and probabilistic programming
Fuente:
arXiv
Saved in:
| Main Author: | Luedtke, Alex |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Adaptive debiased machine learning using data-driven model selection techniques
by: van der Laan, Lars, et al.
Published: (2023)
by: van der Laan, Lars, et al.
Published: (2023)
Doubly robust inference via calibration
by: van der Laan, Lars, et al.
Published: (2024)
by: van der Laan, Lars, et al.
Published: (2024)
DoubleGen: Debiased Generative Modeling of Counterfactuals
by: Luedtke, Alex, et al.
Published: (2025)
by: Luedtke, Alex, et al.
Published: (2025)
Conditional Distributional Treatment Effects: Doubly Robust Estimation and Testing
by: Jain, Saksham, et al.
Published: (2026)
by: Jain, Saksham, et al.
Published: (2026)
Sinkhorn Treatment Effects: A Causal Optimal Transport Measure
by: Agarwal, Medha, et al.
Published: (2026)
by: Agarwal, Medha, et al.
Published: (2026)
Stabilized Inverse Probability Weighting via Isotonic Calibration
by: van der Laan, Lars, et al.
Published: (2024)
by: van der Laan, Lars, et al.
Published: (2024)
Automatic debiasing of neural networks via moment-constrained learning
by: Hines, Christian L., et al.
Published: (2024)
by: Hines, Christian L., et al.
Published: (2024)
Combining T-learning and DR-learning: a framework for oracle-efficient estimation of causal contrasts
by: van der Laan, Lars, et al.
Published: (2024)
by: van der Laan, Lars, et al.
Published: (2024)
Entropy regularization in probabilistic clustering
by: Franzolini, Beatrice, et al.
Published: (2023)
by: Franzolini, Beatrice, et al.
Published: (2023)
Inference on Variable Importance for Treatment Effect Heterogeneity: Shapley Values and Beyond
by: Morzywolek, Pawel, et al.
Published: (2025)
by: Morzywolek, Pawel, et al.
Published: (2025)
Automatic Debiased Machine Learning for Smooth Functionals of Nonparametric M-Estimands
by: van der Laan, Lars, et al.
Published: (2025)
by: van der Laan, Lars, et al.
Published: (2025)
Amortised and provably-robust simulation-based inference
by: Bharti, Ayush, et al.
Published: (2026)
by: Bharti, Ayush, et al.
Published: (2026)
Misspecification-robust likelihood-free inference in high dimensions
by: Thomas, Owen, et al.
Published: (2020)
by: Thomas, Owen, et al.
Published: (2020)
Approximate Bayesian inference for cumulative probit regression models
by: Aliverti, Emanuele
Published: (2025)
by: Aliverti, Emanuele
Published: (2025)
Simulation-based Bayesian inference under model misspecification
by: Kelly, Ryan P., et al.
Published: (2025)
by: Kelly, Ryan P., et al.
Published: (2025)
Partially factorized variational inference for high-dimensional mixed models
by: Goplerud, Max, et al.
Published: (2023)
by: Goplerud, Max, et al.
Published: (2023)
Fast post-process Bayesian inference with Variational Sparse Bayesian Quadrature
by: Li, Chengkun, et al.
Published: (2023)
by: Li, Chengkun, 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)
by: Häggström, Henrik, et al.
Published: (2025)
Statistical inference after variable selection in Cox models: A simulation study
by: Schemet, Lena, et al.
Published: (2026)
by: Schemet, Lena, et al.
Published: (2026)
Monte Carlo inference for semiparametric Bayesian regression
by: Kowal, Daniel R., et al.
Published: (2023)
by: Kowal, Daniel R., et al.
Published: (2023)
Deep classifier kriging for probabilistic spatial prediction of air quality index
by: Chen, Junyu, et al.
Published: (2025)
by: Chen, Junyu, et al.
Published: (2025)
I-trustworthy Models. A framework for trustworthiness evaluation of probabilistic classifiers
by: Vashistha, Ritwik, et al.
Published: (2025)
by: Vashistha, Ritwik, et al.
Published: (2025)
Simulation-based inference via telescoping ratio estimation for trawl processes
by: Leonte, Dan, et al.
Published: (2025)
by: Leonte, Dan, et al.
Published: (2025)
Autotune: fast, accurate, and automatic tuning parameter selection for Lasso
by: Sadhukhan, Tathagata, et al.
Published: (2025)
by: Sadhukhan, Tathagata, et al.
Published: (2025)
Gower's similarity coefficients with automatic weight selection
by: D'Orazio, Marcello
Published: (2024)
by: D'Orazio, Marcello
Published: (2024)
Statistical inference for case-control logistic regression via integrating external summary data
by: Shi, Hengchao, et al.
Published: (2024)
by: Shi, Hengchao, et al.
Published: (2024)
Transductive conformal inference with adaptive scores
by: Gazin, Ulysse, et al.
Published: (2023)
by: Gazin, Ulysse, et al.
Published: (2023)
Collaborative causal inference on distributed data
by: Kawamata, Yuji, et al.
Published: (2022)
by: Kawamata, Yuji, et al.
Published: (2022)
A partial likelihood approach to tree-based density modeling and its application in Bayesian inference
by: Ma, Li, et al.
Published: (2024)
by: Ma, Li, et al.
Published: (2024)
An intuitive rearranging of the Yates covariance decomposition for probabilistic verification of forecasts with the Brier score
by: Vieira, Bruno Hebling
Published: (2026)
by: Vieira, Bruno Hebling
Published: (2026)
Stability Selection via Variable Decorrelation
by: Nouraie, Mahdi, et al.
Published: (2025)
by: Nouraie, Mahdi, et al.
Published: (2025)
Efficient Estimation Under Data Fusion
by: Li, Sijia, et al.
Published: (2021)
by: Li, Sijia, et al.
Published: (2021)
Hypergraph Generation via Structured Stochastic Diffusion
by: Nemeth, Christopher
Published: (2026)
by: Nemeth, Christopher
Published: (2026)
Predictive variational inference: Learn the predictively optimal posterior distribution
by: Lai, Jinlin, et al.
Published: (2024)
by: Lai, Jinlin, et al.
Published: (2024)
Tree-based variational inference for Poisson log-normal models
by: Chaussard, Alexandre, et al.
Published: (2024)
by: Chaussard, Alexandre, et al.
Published: (2024)
Causal inference using invariant prediction: identification and confidence intervals
by: Peters, Jonas, et al.
Published: (2015)
by: Peters, Jonas, et al.
Published: (2015)
Neural variational inference for cutting feedback during uncertainty propagation
by: Song, Jiafang, et al.
Published: (2025)
by: Song, Jiafang, et al.
Published: (2025)
Simulation-based Inference via Langevin Dynamics with Score Matching
by: Jiang, Haoyu, et al.
Published: (2025)
by: Jiang, Haoyu, et al.
Published: (2025)
Conditional Distribution Compression via the Kernel Conditional Mean Embedding
by: Broadbent, Dominic, et al.
Published: (2025)
by: Broadbent, Dominic, et al.
Published: (2025)
Scalable Vertical Federated Learning via Data Augmentation and Amortized Inference
by: Hassan, Conor, et al.
Published: (2024)
by: Hassan, Conor, et al.
Published: (2024)
Similar Items
-
Adaptive debiased machine learning using data-driven model selection techniques
by: van der Laan, Lars, et al.
Published: (2023) -
Doubly robust inference via calibration
by: van der Laan, Lars, et al.
Published: (2024) -
DoubleGen: Debiased Generative Modeling of Counterfactuals
by: Luedtke, Alex, et al.
Published: (2025) -
Conditional Distributional Treatment Effects: Doubly Robust Estimation and Testing
by: Jain, Saksham, et al.
Published: (2026) -
Sinkhorn Treatment Effects: A Causal Optimal Transport Measure
by: Agarwal, Medha, et al.
Published: (2026)