Counterfactual Credit Guided Bayesian Optimization
Fuente:
arXiv
Saved in:
| Main Authors: | Wei, Qiyu, Wang, Haowei, Allmendinger, Richard, Álvarez, Mauricio A. |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Gradient-based Sample Selection for Faster Bayesian Optimization
by: Wei, Qiyu, et al.
Published: (2025)
by: Wei, Qiyu, et al.
Published: (2025)
Regret-Based $(ε,δ)$-optimal Stopping Criteria for Bayesian Optimization
by: Wang, Haowei, et al.
Published: (2026)
by: Wang, Haowei, et al.
Published: (2026)
An adaptive approach to Bayesian Optimization with switching costs
by: Pricopie, Stefan, et al.
Published: (2024)
by: Pricopie, Stefan, et al.
Published: (2024)
Bayesian Generative Adversarial Networks via Gaussian Approximation for Tabular Data Synthesis
by: Nasution, Bahrul Ilmi, et al.
Published: (2026)
by: Nasution, Bahrul Ilmi, et al.
Published: (2026)
Barriers to Counterfactual Credit Attribution for Autoregressive Models
by: Cohen, Aloni, et al.
Published: (2026)
by: Cohen, Aloni, et al.
Published: (2026)
Bayesian Optimization with Expected Improvement: No Regret and the Choice of Incumbent
by: Wang, Jingyi, et al.
Published: (2025)
by: Wang, Jingyi, et al.
Published: (2025)
On Improved Regret Bounds In Bayesian Optimization with Gaussian Noise
by: Wang, Jingyi, et al.
Published: (2024)
by: Wang, Jingyi, et al.
Published: (2024)
Spatial-Aware Decision-Making with Ring Attractors in Reinforcement Learning Systems
by: Saura, Marcos Negre, et al.
Published: (2024)
by: Saura, Marcos Negre, et al.
Published: (2024)
On the convergence rate of noisy Bayesian Optimization with Expected Improvement
by: Wang, Jingyi, et al.
Published: (2025)
by: Wang, Jingyi, et al.
Published: (2025)
ExLLM: Experience-Enhanced LLM Optimization for Molecular Design and Beyond
by: Ran, Nian, et al.
Published: (2025)
by: Ran, Nian, et al.
Published: (2025)
Model-agnostic variable importance for predictive uncertainty: an entropy-based approach
by: Wood, Danny, et al.
Published: (2023)
by: Wood, Danny, et al.
Published: (2023)
Reducing Credit Assignment Variance via Counterfactual Reasoning Paths
by: Ding, Fei, et al.
Published: (2026)
by: Ding, Fei, et al.
Published: (2026)
Protein Counterfactuals via Diffusion-Guided Latent Optimization
by: Kłos, Weronika, et al.
Published: (2026)
by: Kłos, Weronika, et al.
Published: (2026)
COSAC: Counterfactual Credit Assignment in Sequential Cooperative Teams
by: Deshmukh, Shripad, et al.
Published: (2026)
by: Deshmukh, Shripad, et al.
Published: (2026)
TAR: Teacher-Aligned Representations via Contrastive Learning for Quadrupedal Locomotion
by: Mousa, Amr, et al.
Published: (2025)
by: Mousa, Amr, et al.
Published: (2025)
DGPO: Distribution Guided Policy Optimization for Fine Grained Credit Assignment
by: Jin, Hongbo, et al.
Published: (2026)
by: Jin, Hongbo, et al.
Published: (2026)
Constraint-Reduced MILP with Local Outlier Factor Modeling for Plausible Counterfactual Explanations in Credit Approval
by: Thanh, Trung Nguyen, et al.
Published: (2025)
by: Thanh, Trung Nguyen, et al.
Published: (2025)
MIRACL: A Diverse Meta-Reinforcement Learning for Multi-Objective Multi-Echelon Combinatorial Supply Chain Optimisation
by: Rachman, Rifny, et al.
Published: (2026)
by: Rachman, Rifny, et al.
Published: (2026)
Adjusted Expected Improvement for Cumulative Regret Minimization in Noisy Bayesian Optimization
by: Hu, Shouri, et al.
Published: (2022)
by: Hu, Shouri, et al.
Published: (2022)
Flow Matching for Tabular Data Synthesis
by: Nasution, Bahrul Ilmi, et al.
Published: (2025)
by: Nasution, Bahrul Ilmi, et al.
Published: (2025)
Counterfactual Explanations of Black-box Machine Learning Models using Causal Discovery with Applications to Credit Rating
by: Takahashi, Daisuke, et al.
Published: (2024)
by: Takahashi, Daisuke, et al.
Published: (2024)
UGCE: User-Guided Incremental Counterfactual Exploration
by: Fragkathoulas, Christos, et al.
Published: (2025)
by: Fragkathoulas, Christos, et al.
Published: (2025)
Deep Latent Force Models: ODE-based Process Convolutions for Bayesian Deep Learning
by: Baldwin-McDonald, Thomas, et al.
Published: (2023)
by: Baldwin-McDonald, Thomas, et al.
Published: (2023)
Bayesian Intervention Optimization for Causal Discovery
by: Wang, Yuxuan, et al.
Published: (2024)
by: Wang, Yuxuan, et al.
Published: (2024)
A General Framework for User-Guided Bayesian Optimization
by: Hvarfner, Carl, et al.
Published: (2023)
by: Hvarfner, Carl, et al.
Published: (2023)
Non-Linear Counterfactual Aggregate Optimization
by: Heymann, Benjamin, et al.
Published: (2025)
by: Heymann, Benjamin, et al.
Published: (2025)
Decision Focused Causal Learning for Direct Counterfactual Marketing Optimization
by: Zhou, Hao, et al.
Published: (2024)
by: Zhou, Hao, et al.
Published: (2024)
HR-Extreme: A High-Resolution Dataset for Extreme Weather Forecasting
by: Ran, Nian, et al.
Published: (2024)
by: Ran, Nian, et al.
Published: (2024)
Beyond Uniform Credit: Causal Credit Assignment for Policy Optimization
by: Khandoga, Mykola, et al.
Published: (2026)
by: Khandoga, Mykola, et al.
Published: (2026)
Counterfactual Explanations for Linear Optimization
by: Kurtz, Jannis, et al.
Published: (2024)
by: Kurtz, Jannis, et al.
Published: (2024)
Counterfactual Situation Testing: From Single to Multidimensional Discrimination
by: Alvarez, Jose M., et al.
Published: (2025)
by: Alvarez, Jose M., et al.
Published: (2025)
Info-CELS: Informative Saliency Map Guided Counterfactual Explanation
by: Li, Peiyu, et al.
Published: (2024)
by: Li, Peiyu, et al.
Published: (2024)
Memory-Guided Trust-Region Bayesian Optimization (MG-TuRBO) for High Dimensions
by: Saroj, Abhilasha, et al.
Published: (2026)
by: Saroj, Abhilasha, et al.
Published: (2026)
Rethinking Trust Region Bayesian Optimization in High Dimensions
by: Tang, Wei-Ting, et al.
Published: (2026)
by: Tang, Wei-Ting, et al.
Published: (2026)
Automated Flow Pattern Classification in Multi-phase Systems Using AI and Capacitance Sensing Techniques
by: Ran, Nian, et al.
Published: (2025)
by: Ran, Nian, et al.
Published: (2025)
Tabular Diffusion Counterfactual Explanations
by: Zhang, Wei, et al.
Published: (2025)
by: Zhang, Wei, et al.
Published: (2025)
A Guide to Bayesian Optimization in Bioprocess Engineering
by: Siska, Maximilian, et al.
Published: (2025)
by: Siska, Maximilian, et al.
Published: (2025)
Multi-objective evolutionary GAN for tabular data synthesis
by: Ran, Nian, et al.
Published: (2024)
by: Ran, Nian, et al.
Published: (2024)
Provably Robust Bayesian Counterfactual Explanations under Model Changes
by: Duell, Jamie, et al.
Published: (2026)
by: Duell, Jamie, et al.
Published: (2026)
Human Preferences in Large Language Model Latent Space: A Technical Analysis on the Reliability of Synthetic Data in Voting Outcome Prediction
by: Ball, Sarah, et al.
Published: (2025)
by: Ball, Sarah, et al.
Published: (2025)
Similar Items
-
Gradient-based Sample Selection for Faster Bayesian Optimization
by: Wei, Qiyu, et al.
Published: (2025) -
Regret-Based $(ε,δ)$-optimal Stopping Criteria for Bayesian Optimization
by: Wang, Haowei, et al.
Published: (2026) -
An adaptive approach to Bayesian Optimization with switching costs
by: Pricopie, Stefan, et al.
Published: (2024) -
Bayesian Generative Adversarial Networks via Gaussian Approximation for Tabular Data Synthesis
by: Nasution, Bahrul Ilmi, et al.
Published: (2026) -
Barriers to Counterfactual Credit Attribution for Autoregressive Models
by: Cohen, Aloni, et al.
Published: (2026)