Training data membership inference via Gaussian process meta-modeling: a post-hoc analysis approach
Fuente:
arXiv
Saved in:
| Main Authors: | Huang, Yongchao, Zhang, Pengfei, Mumtaz, Shahzad |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Electrostatics-based particle sampling and approximate inference
by: Huang, Yongchao
Published: (2024)
by: Huang, Yongchao
Published: (2024)
Bayesian Inference of Training Dataset Membership
by: Huang, Yongchao
Published: (2025)
by: Huang, Yongchao
Published: (2025)
Exploring the limits of strong membership inference attacks on large language models
by: Hayes, Jamie, et al.
Published: (2025)
by: Hayes, Jamie, et al.
Published: (2025)
Variational Inference via Smoothed Particle Hydrodynamics
by: Huang, Yongchao
Published: (2024)
by: Huang, Yongchao
Published: (2024)
Revisiting the robustness of post-hoc interpretability methods
by: Wei, Jiawen, et al.
Published: (2024)
by: Wei, Jiawen, et al.
Published: (2024)
A new membership inference attack that spots memorization in generative and predictive models: Loss-Based with Reference Model algorithm (LBRM)
by: Taleb, Faiz, et al.
Published: (2025)
by: Taleb, Faiz, et al.
Published: (2025)
A redescription mining framework for post-hoc explaining and relating deep learning models
by: Mihelčić, Matej, et al.
Published: (2025)
by: Mihelčić, Matej, et al.
Published: (2025)
Variational Inference Using Material Point Method
by: Huang, Yongchao
Published: (2024)
by: Huang, Yongchao
Published: (2024)
Training Verification-Friendly Neural Networks via Neuron Behavior Consistency
by: Liu, Zongxin, et al.
Published: (2024)
by: Liu, Zongxin, et al.
Published: (2024)
Evaluation of post-hoc interpretability methods in time-series classification
by: Turbé, Hugues, et al.
Published: (2022)
by: Turbé, Hugues, et al.
Published: (2022)
In defence of post-hoc explanations in medical AI
by: Hatherley, Joshua, et al.
Published: (2025)
by: Hatherley, Joshua, et al.
Published: (2025)
LVM-GP: Uncertainty-Aware PDE Solver via coupling latent variable model and Gaussian process
by: Feng, Xiaodong, et al.
Published: (2025)
by: Feng, Xiaodong, et al.
Published: (2025)
PXGen: A Post-hoc Explainable Method for Generative Models
by: Huang, Yen-Lung, et al.
Published: (2025)
by: Huang, Yen-Lung, et al.
Published: (2025)
In Defence of Post-hoc Explainability
by: Oh, Nick
Published: (2024)
by: Oh, Nick
Published: (2024)
An AI-powered Bayesian generative modeling approach for causal inference in observational studies
by: Liu, Qiao, et al.
Published: (2025)
by: Liu, Qiao, et al.
Published: (2025)
Post-hoc Interpretability Illumination for Scientific Interaction Discovery
by: Zhang, Ling, et al.
Published: (2024)
by: Zhang, Ling, et al.
Published: (2024)
Diffusion model for relational inference
by: Zheng, Shuhan, et al.
Published: (2024)
by: Zheng, Shuhan, et al.
Published: (2024)
Rotated Runtime Smooth: Training-Free Activation Smoother for accurate INT4 inference
by: Yi, Ke, et al.
Published: (2024)
by: Yi, Ke, et al.
Published: (2024)
Training data attribution in diffusion models via mirrored unlearning and noise-consistent skew
by: Serrà, Joan, et al.
Published: (2026)
by: Serrà, Joan, et al.
Published: (2026)
It Takes a Good Model to Train a Good Model: Generalized Gaussian Priors for Optimized LLMs
by: Wu, Jun, et al.
Published: (2025)
by: Wu, Jun, et al.
Published: (2025)
Flow based approach for Dynamic Temporal Causal models with non-Gaussian or Heteroscedastic Noises
by: Rahmani, Abdellah, et al.
Published: (2025)
by: Rahmani, Abdellah, et al.
Published: (2025)
Fuzzy Logic Function as a Post-hoc Explanator of the Nonlinear Classifier
by: Klimo, Martin, et al.
Published: (2024)
by: Klimo, Martin, et al.
Published: (2024)
Unlocking Post-hoc Dataset Inference with Synthetic Data
by: Zhao, Bihe, et al.
Published: (2025)
by: Zhao, Bihe, et al.
Published: (2025)
Unifying Post-hoc Explanations of Knowledge Graph Completions
by: Lonardi, Alessandro, et al.
Published: (2025)
by: Lonardi, Alessandro, et al.
Published: (2025)
Stream-level flow matching with Gaussian processes
by: Wei, Ganchao, et al.
Published: (2024)
by: Wei, Ganchao, et al.
Published: (2024)
PHLoRA: data-free Post-hoc Low-Rank Adapter extraction from full-rank checkpoint
by: Vasani, Bhoomit, et al.
Published: (2025)
by: Vasani, Bhoomit, et al.
Published: (2025)
Manipulating hidden-Markov-model inferences by corrupting batch data
by: Caballero, William N., et al.
Published: (2024)
by: Caballero, William N., et al.
Published: (2024)
Informative Perturbation Selection for Uncertainty-Aware Post-hoc Explanations
by: Chugh, Sumedha, et al.
Published: (2026)
by: Chugh, Sumedha, et al.
Published: (2026)
The Effect of Model Size on LLM Post-hoc Explainability via LIME
by: Heyen, Henning, et al.
Published: (2024)
by: Heyen, Henning, et al.
Published: (2024)
Bias Is a Subspace, Not a Coordinate: A Geometric Rethinking of Post-hoc Debiasing in Vision-Language Models
by: Zhao, Dachuan, et al.
Published: (2025)
by: Zhao, Dachuan, et al.
Published: (2025)
Explaining Neural Networks in Preference Learning: a Post-hoc Inductive Logic Programming Approach
by: Fossemò, Daniele, et al.
Published: (2026)
by: Fossemò, Daniele, et al.
Published: (2026)
LLM enhanced graph inference for long-term disease progression modelling
by: He, Tiantian, et al.
Published: (2025)
by: He, Tiantian, et al.
Published: (2025)
Diffusion Tree Sampling: Scalable inference-time alignment of diffusion models
by: Jain, Vineet, et al.
Published: (2025)
by: Jain, Vineet, et al.
Published: (2025)
BrainHGT: A Hierarchical Graph Transformer for Interpretable Brain Network Analysis
by: Ma, Jiajun, et al.
Published: (2025)
by: Ma, Jiajun, et al.
Published: (2025)
The future of human-centric eXplainable Artificial Intelligence (XAI) is not post-hoc explanations
by: Swamy, Vinitra, et al.
Published: (2023)
by: Swamy, Vinitra, et al.
Published: (2023)
DeepCDCL: An CDCL-based Neural Network Verification Framework
by: Liu, Zongxin, et al.
Published: (2024)
by: Liu, Zongxin, et al.
Published: (2024)
Efficient Agent Training for Computer Use
by: He, Yanheng, et al.
Published: (2025)
by: He, Yanheng, et al.
Published: (2025)
Understanding Post-hoc Explainers: The Case of Anchors
by: Lopardo, Gianluigi, et al.
Published: (2023)
by: Lopardo, Gianluigi, et al.
Published: (2023)
Explaining Time Series Classifiers with PHAR: Rule Extraction and Fusion from Post-hoc Attributions
by: Mozolewski, Maciej, et al.
Published: (2025)
by: Mozolewski, Maciej, et al.
Published: (2025)
Evidential Transformation Network: Turning Pretrained Models into Evidential Models for Post-hoc Uncertainty Estimation
by: Chun, Yongchan, et al.
Published: (2026)
by: Chun, Yongchan, et al.
Published: (2026)
Similar Items
-
Electrostatics-based particle sampling and approximate inference
by: Huang, Yongchao
Published: (2024) -
Bayesian Inference of Training Dataset Membership
by: Huang, Yongchao
Published: (2025) -
Exploring the limits of strong membership inference attacks on large language models
by: Hayes, Jamie, et al.
Published: (2025) -
Variational Inference via Smoothed Particle Hydrodynamics
by: Huang, Yongchao
Published: (2024) -
Revisiting the robustness of post-hoc interpretability methods
by: Wei, Jiawen, et al.
Published: (2024)