Laplace Sample Information: Data Informativeness Through a Bayesian Lens
Fuente:
arXiv
Saved in:
| Main Authors: | Kaiser, Johannes, Schwethelm, Kristian, Rueckert, Daniel, Kaissis, Georgios |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
How Much Is One Recurrence Worth? Iso-Depth Scaling Laws for Looped Language Models
by: Schwethelm, Kristian, et al.
Published: (2026)
by: Schwethelm, Kristian, et al.
Published: (2026)
On Arbitrary Predictions from Equally Valid Models
by: Lockfisch, Sarah, et al.
Published: (2025)
by: Lockfisch, Sarah, et al.
Published: (2025)
Differentially Private Active Learning: Balancing Effective Data Selection and Privacy
by: Schwethelm, Kristian, et al.
Published: (2024)
by: Schwethelm, Kristian, et al.
Published: (2024)
Incentivising the federation: gradient-based metrics for data selection and valuation in private decentralised training
by: Usynin, Dmitrii, et al.
Published: (2023)
by: Usynin, Dmitrii, et al.
Published: (2023)
Beyond the Calibration Point: Mechanism Comparison in Differential Privacy
by: Kaissis, Georgios, et al.
Published: (2024)
by: Kaissis, Georgios, et al.
Published: (2024)
Information-theoretic Bayesian Optimization: Survey and Tutorial
by: Garrido-Merchán, Eduardo C.
Published: (2025)
by: Garrido-Merchán, Eduardo C.
Published: (2025)
Learning Invariant Graph Representations Through Redundant Information
by: Halder, Barproda, et al.
Published: (2025)
by: Halder, Barproda, et al.
Published: (2025)
An Information-Theoretic Criterion for Efficient Data Synthesis
by: Li, Hanyu, et al.
Published: (2026)
by: Li, Hanyu, et al.
Published: (2026)
An Information Criterion for Controlled Disentanglement of Multimodal Data
by: Wang, Chenyu, et al.
Published: (2024)
by: Wang, Chenyu, et al.
Published: (2024)
Partial Information Decomposition for Data Interpretability and Feature Selection
by: Westphal, Charles, et al.
Published: (2024)
by: Westphal, Charles, et al.
Published: (2024)
From Markov to Laplace: How Mamba In-Context Learns Markov Chains
by: Bondaschi, Marco, et al.
Published: (2025)
by: Bondaschi, Marco, et al.
Published: (2025)
Your Privacy Depends on Others: Collusion Vulnerabilities in Individual Differential Privacy
by: Kaiser, Johannes, et al.
Published: (2026)
by: Kaiser, Johannes, et al.
Published: (2026)
Uncertainty Quantification and Data Efficiency in AI: An Information-Theoretic Perspective
by: Simeone, Osvaldo, et al.
Published: (2025)
by: Simeone, Osvaldo, et al.
Published: (2025)
Analyzing and Improving Chain-of-Thought Monitorability Through Information Theory
by: Anwar, Usman, et al.
Published: (2026)
by: Anwar, Usman, et al.
Published: (2026)
Does Privacy Always Harm Fairness? Data-Dependent Trade-offs via Chernoff Information Neural Estimation
by: Nichani, Arjun, et al.
Published: (2026)
by: Nichani, Arjun, et al.
Published: (2026)
Redundancy as a Structural Information Principle for Learning and Generalization
by: Bi, Yuda, et al.
Published: (2025)
by: Bi, Yuda, et al.
Published: (2025)
Unintended Memorization of Sensitive Information in Fine-Tuned Language Models
by: Szep, Marton, et al.
Published: (2026)
by: Szep, Marton, et al.
Published: (2026)
Generalization and Informativeness of Conformal Prediction
by: Zecchin, Matteo, et al.
Published: (2024)
by: Zecchin, Matteo, et al.
Published: (2024)
The Agent Capability Problem: Predicting Solvability Through Information-Theoretic Bounds
by: Lutati, Shahar
Published: (2025)
by: Lutati, Shahar
Published: (2025)
Interpretable Diffusion via Information Decomposition
by: Kong, Xianghao, et al.
Published: (2023)
by: Kong, Xianghao, et al.
Published: (2023)
A Novel Double Pruning method for Imbalanced Data using Information Entropy and Roulette Wheel Selection for Breast Cancer Diagnosis
by: Bacha, Soufiane, et al.
Published: (2025)
by: Bacha, Soufiane, et al.
Published: (2025)
Machine Unlearning via Information Theoretic Regularization
by: Xu, Shizhou, et al.
Published: (2025)
by: Xu, Shizhou, et al.
Published: (2025)
An Effective Information Theoretic Framework for Channel Pruning
by: Chen, Yihao, et al.
Published: (2024)
by: Chen, Yihao, et al.
Published: (2024)
Flexible Variational Information Bottleneck: Achieving Diverse Compression with a Single Training
by: Kudo, Sota, et al.
Published: (2024)
by: Kudo, Sota, et al.
Published: (2024)
Rethinking KV Cache Eviction via a Unified Information-Theoretic Objective
by: Yang, Jiaming, et al.
Published: (2026)
by: Yang, Jiaming, et al.
Published: (2026)
Fairness Overfitting in Machine Learning: An Information-Theoretic Perspective
by: Laakom, Firas, et al.
Published: (2025)
by: Laakom, Firas, et al.
Published: (2025)
A Rational Account of Categorization Based on Information Theory
by: MacLellan, Christopher J., et al.
Published: (2026)
by: MacLellan, Christopher J., et al.
Published: (2026)
Entropy-informed Decoding: Adaptive Information-Driven Branching
by: Evans, Benjamin Patrick, et al.
Published: (2026)
by: Evans, Benjamin Patrick, et al.
Published: (2026)
The Causal Information Bottleneck and Optimal Causal Variable Abstractions
by: Simoes, Francisco N. F. Q., et al.
Published: (2024)
by: Simoes, Francisco N. F. Q., et al.
Published: (2024)
Information-Theoretic State Variable Selection for Reinforcement Learning
by: Westphal, Charles, et al.
Published: (2024)
by: Westphal, Charles, et al.
Published: (2024)
General Information Metrics for Improving AI Model Training Efficiency
by: Xu, Jianfeng, et al.
Published: (2025)
by: Xu, Jianfeng, et al.
Published: (2025)
Broadcast Channel Cooperative Gain: An Operational Interpretation of Partial Information Decomposition
by: Tian, Chao, et al.
Published: (2025)
by: Tian, Chao, et al.
Published: (2025)
Generalization and Informativeness of Weighted Conformal Risk Control Under Covariate Shift
by: Zecchin, Matteo, et al.
Published: (2025)
by: Zecchin, Matteo, et al.
Published: (2025)
The Causal Description Gap: Information-Theoretic Separations Across Pearl's Hierarchy
by: Emadi, Seyed Morteza
Published: (2026)
by: Emadi, Seyed Morteza
Published: (2026)
Neural Estimation of Pairwise Mutual Information in Masked Discrete Sequence Models
by: Sharma, Jai, et al.
Published: (2026)
by: Sharma, Jai, et al.
Published: (2026)
Context Channel Capacity: An Information-Theoretic Framework for Understanding Catastrophic Forgetting
by: Cheng, Ran
Published: (2026)
by: Cheng, Ran
Published: (2026)
GeoIB: Geometry-Aware Information Bottleneck via Statistical-Manifold Compression
by: Wang, Weiqi, et al.
Published: (2026)
by: Wang, Weiqi, et al.
Published: (2026)
Latent Representation and Simulation of Markov Processes via Time-Lagged Information Bottleneck
by: Federici, Marco, et al.
Published: (2023)
by: Federici, Marco, et al.
Published: (2023)
Information-Guided Diffusion Sampling for Dataset Distillation
by: Ye, Linfeng, et al.
Published: (2025)
by: Ye, Linfeng, et al.
Published: (2025)
Greedy Sampling Is Provably Efficient for RLHF
by: Wu, Di, et al.
Published: (2025)
by: Wu, Di, et al.
Published: (2025)
Similar Items
-
How Much Is One Recurrence Worth? Iso-Depth Scaling Laws for Looped Language Models
by: Schwethelm, Kristian, et al.
Published: (2026) -
On Arbitrary Predictions from Equally Valid Models
by: Lockfisch, Sarah, et al.
Published: (2025) -
Differentially Private Active Learning: Balancing Effective Data Selection and Privacy
by: Schwethelm, Kristian, et al.
Published: (2024) -
Incentivising the federation: gradient-based metrics for data selection and valuation in private decentralised training
by: Usynin, Dmitrii, et al.
Published: (2023) -
Beyond the Calibration Point: Mechanism Comparison in Differential Privacy
by: Kaissis, Georgios, et al.
Published: (2024)