Saved in:
| Main Authors: | Dong, Jinzong, Jiang, Zhaohui, Pan, Dong, Yu, Haoyang |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2412.10658 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Expectation Consistency Loss: Rethink Confidence Calibration under Covariate Shift
by: Dong, Jinzong, et al.
Published: (2026)
by: Dong, Jinzong, et al.
Published: (2026)
Confidence Calibration under Ambiguous Ground Truth
by: Tao, Linwei, et al.
Published: (2026)
by: Tao, Linwei, et al.
Published: (2026)
LLMs are Overconfident: Evaluating Confidence Interval Calibration with FermiEval
by: Epstein, Elliot L., et al.
Published: (2025)
by: Epstein, Elliot L., et al.
Published: (2025)
Beyond Accuracy: Are Time Series Foundation Models Well-Calibrated?
by: Adler, Coen, et al.
Published: (2025)
by: Adler, Coen, et al.
Published: (2025)
Proximal Action Replacement for Behavior Cloning Actor-Critic in Offline Reinforcement Learning
by: Dong, Jinzong, et al.
Published: (2026)
by: Dong, Jinzong, et al.
Published: (2026)
HOLOGRAPH: Active Causal Discovery via Sheaf-Theoretic Alignment of Large Language Model Priors
by: Kim, Hyunjun
Published: (2025)
by: Kim, Hyunjun
Published: (2025)
Mind the GAP: Improving Robustness to Subpopulation Shifts with Group-Aware Priors
by: Rudner, Tim G. J., et al.
Published: (2024)
by: Rudner, Tim G. J., et al.
Published: (2024)
Multi-Teacher Knowledge Distillation via Teacher-Informed Mixture Priors
by: Fang, Luyang, et al.
Published: (2026)
by: Fang, Luyang, et al.
Published: (2026)
Goal-Oriented Sequential Bayesian Experimental Design for Causal Learning
by: Zhang, Zheyu, et al.
Published: (2025)
by: Zhang, Zheyu, et al.
Published: (2025)
CafeMed: Causal Attention Fusion Enhanced Medication Recommendation
by: Ren, Kelin, et al.
Published: (2025)
by: Ren, Kelin, et al.
Published: (2025)
Uncertainty Quantification for Prior-Data Fitted Networks using Martingale Posteriors
by: Nagler, Thomas, et al.
Published: (2025)
by: Nagler, Thomas, et al.
Published: (2025)
Propagation and Pitfalls: Reasoning-based Assessment of Knowledge Editing through Counterfactual Tasks
by: Hua, Wenyue, et al.
Published: (2024)
by: Hua, Wenyue, et al.
Published: (2024)
A Framework for Nonstationary Gaussian Processes with Neural Network Parameters
by: James, Zachary, et al.
Published: (2025)
by: James, Zachary, et al.
Published: (2025)
A Double Machine Learning Approach to Combining Experimental and Observational Data
by: Parikh, Harsh, et al.
Published: (2023)
by: Parikh, Harsh, et al.
Published: (2023)
ProCause: Generating Counterfactual Outcomes to Evaluate Prescriptive Process Monitoring Methods
by: De Moor, Jakob, et al.
Published: (2025)
by: De Moor, Jakob, et al.
Published: (2025)
Model-Free Assessment of Simulator Fidelity via Quantile Curves
by: Iyengar, Garud, et al.
Published: (2025)
by: Iyengar, Garud, et al.
Published: (2025)
Effective Causal Discovery under Identifiable Heteroscedastic Noise Model
by: Yin, Naiyu, et al.
Published: (2023)
by: Yin, Naiyu, et al.
Published: (2023)
Integrating Random Forests and Generalized Linear Models for Improved Accuracy and Interpretability
by: Agarwal, Abhineet, et al.
Published: (2023)
by: Agarwal, Abhineet, et al.
Published: (2023)
When Graph Neural Network Meets Causality: Opportunities, Methodologies and An Outlook
by: Jiang, Wenzhao, et al.
Published: (2023)
by: Jiang, Wenzhao, et al.
Published: (2023)
Fair Risk Control: A Generalized Framework for Calibrating Multi-group Fairness Risks
by: Zhang, Lujing, et al.
Published: (2024)
by: Zhang, Lujing, et al.
Published: (2024)
Evaluating the Effectiveness of Index-Based Treatment Allocation
by: Boehmer, Niclas, et al.
Published: (2024)
by: Boehmer, Niclas, et al.
Published: (2024)
Transformer-Based Spatial-Temporal Counterfactual Outcomes Estimation
by: Li, He, et al.
Published: (2025)
by: Li, He, et al.
Published: (2025)
Modeling and Discovering Direct Causes for Predictive Models
by: Chen, Yizuo, et al.
Published: (2024)
by: Chen, Yizuo, et al.
Published: (2024)
PCS Workflow for Veridical Data Science in the Age of AI
by: Rewolinski, Zachary T., et al.
Published: (2025)
by: Rewolinski, Zachary T., et al.
Published: (2025)
Causal and Local Correlations Based Network for Multivariate Time Series Classification
by: Du, Mingsen, et al.
Published: (2024)
by: Du, Mingsen, 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)
Censoring-Aware Tree-Based Reinforcement Learning for Estimating Dynamic Treatment Regimes with Censored Outcomes
by: Paul, Animesh Kumar, et al.
Published: (2025)
by: Paul, Animesh Kumar, et al.
Published: (2025)
Uplift Modeling Under Limited Supervision
by: Panagopoulos, George, et al.
Published: (2024)
by: Panagopoulos, George, et al.
Published: (2024)
Compositional Models for Estimating Causal Effects
by: Pruthi, Purva, et al.
Published: (2024)
by: Pruthi, Purva, et al.
Published: (2024)
Counterfactual Probabilistic Diffusion with Expert Models
by: Mu, Wenhao, et al.
Published: (2025)
by: Mu, Wenhao, et al.
Published: (2025)
Flexible Counterfactual Explanations with Generative Models
by: Hellemans, Stig, et al.
Published: (2025)
by: Hellemans, Stig, et al.
Published: (2025)
Cardinality-Regularized Hawkes-Granger Model
by: Idé, Tsuyoshi, et al.
Published: (2022)
by: Idé, Tsuyoshi, et al.
Published: (2022)
Partially Observed Structural Causal Models
by: Orujlu, Turan, et al.
Published: (2026)
by: Orujlu, Turan, et al.
Published: (2026)
Causal Identification in Time Series Models
by: Jahn, Erik, et al.
Published: (2025)
by: Jahn, Erik, et al.
Published: (2025)
Augmenting Limited and Biased RCTs through Pseudo-Sample Matching-Based Observational Data Fusion Method
by: Han, Kairong, et al.
Published: (2025)
by: Han, Kairong, et al.
Published: (2025)
Evaluation of Stress Detection as Time Series Events -- A Novel Window-Based F1-Metric
by: Skat-Rørdam, Harald Vilhelm, et al.
Published: (2025)
by: Skat-Rørdam, Harald Vilhelm, et al.
Published: (2025)
Comparing Foundation Models using Data Kernels
by: Duderstadt, Brandon, et al.
Published: (2023)
by: Duderstadt, Brandon, et al.
Published: (2023)
Learning Causal Abstractions of Linear Structural Causal Models
by: Massidda, Riccardo, et al.
Published: (2024)
by: Massidda, Riccardo, et al.
Published: (2024)
Generally-Occurring Model Change for Robust Counterfactual Explanations
by: Xu, Ao, et al.
Published: (2024)
by: Xu, Ao, et al.
Published: (2024)
Multi-Domain Causal Discovery in Bijective Causal Models
by: Jalaldoust, Kasra, et al.
Published: (2025)
by: Jalaldoust, Kasra, et al.
Published: (2025)
Similar Items
-
Expectation Consistency Loss: Rethink Confidence Calibration under Covariate Shift
by: Dong, Jinzong, et al.
Published: (2026) -
Confidence Calibration under Ambiguous Ground Truth
by: Tao, Linwei, et al.
Published: (2026) -
LLMs are Overconfident: Evaluating Confidence Interval Calibration with FermiEval
by: Epstein, Elliot L., et al.
Published: (2025) -
Beyond Accuracy: Are Time Series Foundation Models Well-Calibrated?
by: Adler, Coen, et al.
Published: (2025) -
Proximal Action Replacement for Behavior Cloning Actor-Critic in Offline Reinforcement Learning
by: Dong, Jinzong, et al.
Published: (2026)