Copertina

On Predictive planning and counterfactual learning in active inference

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Paul, Aswin, Isomura, Takuya, Razi, Adeel
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Artificial Intelligence Machine Learning Methodology
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

On efficient computation in active inference
di: Paul, Aswin, et al.
Pubblicazione: (2023)

Estimating counterfactual treatment outcomes over time in complex multiagent scenarios
di: Fujii, Keisuke, et al.
Pubblicazione: (2022)

Explainability as statistical inference
di: Senetaire, Hugo Henri Joseph, et al.
Pubblicazione: (2022)

Post-detection inference for sequential changepoint localization
di: Saha, Aytijhya, et al.
Pubblicazione: (2025)

An AI-powered Bayesian generative modeling approach for causal inference in observational studies
di: Liu, Qiao, et al.
Pubblicazione: (2025)

DoWhy-GCM: An extension of DoWhy for causal inference in graphical causal models
di: Blöbaum, Patrick, et al.
Pubblicazione: (2022)

Length Optimization in Conformal Prediction
di: Kiyani, Shayan, et al.
Pubblicazione: (2024)

Bayesian Hierarchical Invariant Prediction
di: Madaleno, Francisco, et al.
Pubblicazione: (2025)

Prediction-Intervention Games and Invariant Sets
di: Kühne, Linus, et al.
Pubblicazione: (2026)

Conformal Prediction for Causal Effects of Continuous Treatments
di: Schröder, Maresa, et al.
Pubblicazione: (2024)

Modeling and Discovering Direct Causes for Predictive Models
di: Chen, Yizuo, et al.
Pubblicazione: (2024)

Adaptive Experimental Design for Policy Learning
di: Kato, Masahiro, et al.
Pubblicazione: (2024)

Prediction-Powered Inference with Imputed Covariates and Nonuniform Sampling
di: Kluger, Dan M., et al.
Pubblicazione: (2025)

Sample size planning for conditional counterfactual mean estimation with a K-armed randomized experiment
di: Ruiz, Gabriel
Pubblicazione: (2024)

Adaptive Prediction-Powered AutoEval with Reliability and Efficiency Guarantees
di: Park, Sangwoo, et al.
Pubblicazione: (2025)

Conformal Prediction Sets with Improved Conditional Coverage using Trust Scores
di: Kaur, Jivat Neet, et al.
Pubblicazione: (2025)

End-to-End Deep Learning for Predicting Metric Space-Valued Outputs
di: Zhou, Yidong, et al.
Pubblicazione: (2025)

Censoring-Aware Tree-Based Reinforcement Learning for Estimating Dynamic Treatment Regimes with Censored Outcomes
di: Paul, Animesh Kumar, et al.
Pubblicazione: (2025)

A Critical Perspective on Finite Sample Conformal Prediction Theory in Medical Applications
di: Kladny, Klaus-Rudolf, et al.
Pubblicazione: (2025)

Statistical Limits and Efficient Algorithms for Differentially Private Federated Learning
di: Auddy, Arnab, et al.
Pubblicazione: (2026)

Industrializing Prediction-Powered Inference: The GLIDE Library for Reliable GenAI and Agentic Systems Evaluation
di: Martinon, Grégoire, et al.
Pubblicazione: (2026)

Neural Networks Decoded: Targeted and Robust Analysis of Neural Network Decisions via Causal Explanations and Reasoning
di: Diallo, Alec F., et al.
Pubblicazione: (2024)

Scalable Spatiotemporal Prediction with Bayesian Neural Fields
di: Saad, Feras, et al.
Pubblicazione: (2024)

Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization
di: Zhang, Dinghuai, et al.
Pubblicazione: (2023)

Predicting Cellular Responses with Variational Causal Inference and Refined Relational Information
di: Wu, Yulun, et al.
Pubblicazione: (2022)

Black Box Causal Inference: Effect Estimation via Meta Prediction
di: Bynum, Lucius E. J., et al.
Pubblicazione: (2025)

Dynamic planning in hierarchical active inference
di: Priorelli, Matteo, et al.
Pubblicazione: (2024)

On the Unknowable Limits to Prediction
di: Yan, Jiani, et al.
Pubblicazione: (2024)

Private Prediction Sets
di: Angelopoulos, Anastasios N., et al.
Pubblicazione: (2021)

Multivariate Standardized Residuals for Conformal Prediction
di: Braun, Sacha, et al.
Pubblicazione: (2025)

Label Noise Robustness of Conformal Prediction
di: Einbinder, Bat-Sheva, et al.
Pubblicazione: (2022)

Quantile deep learning models for multi-step ahead time series prediction
di: Cheung, Jimmy, et al.
Pubblicazione: (2024)

Bias-Aware Conformal Prediction for Metric-Based Imaging Pipelines
di: Cheung, Matt Y., et al.
Pubblicazione: (2024)

Enhancing Maritime Trajectory Forecasting via H3 Index and Causal Language Modelling (CLM)
di: Drapier, Nicolas, et al.
Pubblicazione: (2024)

Effective Bayesian Causal Inference via Structural Marginalisation and Autoregressive Orders
di: Toth, Christian, et al.
Pubblicazione: (2024)

SKADA-Bench: Benchmarking Unsupervised Domain Adaptation Methods with Realistic Validation On Diverse Modalities
di: Lalou, Yanis, et al.
Pubblicazione: (2024)

Evaluating the Effectiveness of Index-Based Treatment Allocation
di: Boehmer, Niclas, et al.
Pubblicazione: (2024)

DCRMTA: Unbiased Causal Representation for Multi-touch Attribution
di: Tang, Jiaming
Pubblicazione: (2024)

Conformal Diffusion Models for Individual Treatment Effect Estimation and Inference
di: Cai, Hengrui, et al.
Pubblicazione: (2024)

Self-Labeling in Multivariate Causality and Quantification for Adaptive Machine Learning
di: Ren, Yutian, et al.
Pubblicazione: (2024)