si4onnx: A Python package for Selective Inference in Deep Learning Models
Fuente:
arXiv
Saved in:
| Main Authors: | Katsuoka, Teruyuki, Shiraishi, Tomohiro, Miwa, Daiki, Nishino, Shuichi, Takeuchi, Ichiro |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Statistical Test for Saliency Maps of Graph Neural Networks via Selective Inference
by: Nishino, Shuichi, et al.
Published: (2025)
by: Nishino, Shuichi, et al.
Published: (2025)
Post-ADC Inference: Valid Inference After Active Data Collection
by: Nishino, Shuichi, et al.
Published: (2026)
by: Nishino, Shuichi, et al.
Published: (2026)
Statistical Test for Auto Feature Engineering by Selective Inference
by: Matsukawa, Tatsuya, et al.
Published: (2024)
by: Matsukawa, Tatsuya, et al.
Published: (2024)
Quantifying Statistical Significance of Deep Nearest Neighbor Anomaly Detection via Selective Inference
by: Niihori, Mizuki, et al.
Published: (2025)
by: Niihori, Mizuki, et al.
Published: (2025)
Statistical Test for Diffusion-Based Anomaly Localization via Selective Inference
by: Katsuoka, Teruyuki, et al.
Published: (2024)
by: Katsuoka, Teruyuki, et al.
Published: (2024)
Change Point Detection in the Frequency Domain with Statistical Reliability
by: Yamada, Akifumi, et al.
Published: (2025)
by: Yamada, Akifumi, et al.
Published: (2025)
Statistical Test for Anomaly Detections by Variational Auto-Encoders
by: Miwa, Daiki, et al.
Published: (2024)
by: Miwa, Daiki, et al.
Published: (2024)
Statistical Test for Feature Selection Pipelines by Selective Inference
by: Shiraishi, Tomohiro, et al.
Published: (2024)
by: Shiraishi, Tomohiro, et al.
Published: (2024)
Statistical Testing Framework for Clustering Pipelines by Selective Inference
by: Miyata, Yugo, et al.
Published: (2026)
by: Miyata, Yugo, et al.
Published: (2026)
Statistical Test for Attention Map in Vision Transformer
by: Shiraishi, Tomohiro, et al.
Published: (2024)
by: Shiraishi, Tomohiro, et al.
Published: (2024)
Safe RuleFit: Learning Optimal Sparse Rule Model by Meta Safe Screening
by: Kato, Hiroki, et al.
Published: (2018)
by: Kato, Hiroki, et al.
Published: (2018)
Bayesian Optimization for Simultaneous Selection of Machine Learning Algorithms and Hyperparameters on Shared Latent Space
by: Ishikawa, Kazuki, et al.
Published: (2025)
by: Ishikawa, Kazuki, et al.
Published: (2025)
Latent Space Bayesian Optimization with Latent Data Augmentation for Enhanced Exploration
by: Boyar, Onur, et al.
Published: (2023)
by: Boyar, Onur, et al.
Published: (2023)
Statistical testing on generative AI anomaly detection tools in Alzheimer's Disease diagnosis
by: He, Rosemary, et al.
Published: (2024)
by: He, Rosemary, et al.
Published: (2024)
Effector: A Python package for regional explanations
by: Gkolemis, Vasilis, et al.
Published: (2024)
by: Gkolemis, Vasilis, et al.
Published: (2024)
Safe Distributionally Robust Feature Selection under Covariate Shift
by: Hanada, Hiroyuki, et al.
Published: (2026)
by: Hanada, Hiroyuki, et al.
Published: (2026)
Active Learning for Level Set Estimation Using Randomized Straddle Algorithms
by: Inatsu, Yu, et al.
Published: (2024)
by: Inatsu, Yu, et al.
Published: (2024)
dlordinal: a Python package for deep ordinal classification
by: Bérchez-Moreno, Francisco, et al.
Published: (2024)
by: Bérchez-Moreno, Francisco, et al.
Published: (2024)
Randomized Kriging Believer for Parallel Bayesian Optimization with Regret Bounds
by: Sugiura, Shuhei, et al.
Published: (2026)
by: Sugiura, Shuhei, et al.
Published: (2026)
nabqr: Python package for improving probabilistic forecasts
by: Jørgensena, Bastian Schmidt, et al.
Published: (2025)
by: Jørgensena, Bastian Schmidt, et al.
Published: (2025)
HiGP: A high-performance Python package for Gaussian Process
by: Huang, Hua, et al.
Published: (2025)
by: Huang, Hua, et al.
Published: (2025)
ml_edm package: a Python toolkit for Machine Learning based Early Decision Making
by: Renault, Aurélien, et al.
Published: (2024)
by: Renault, Aurélien, et al.
Published: (2024)
The Gaussian-Linear Hidden Markov model: a Python package
by: Vidaurre, Diego, et al.
Published: (2023)
by: Vidaurre, Diego, et al.
Published: (2023)
Regret Analysis of Posterior Sampling-Based Expected Improvement for Bayesian Optimization
by: Takeno, Shion, et al.
Published: (2025)
by: Takeno, Shion, et al.
Published: (2025)
Conditional Latent Space Molecular Scaffold Optimization for Accelerated Molecular Design
by: Boyar, Onur, et al.
Published: (2024)
by: Boyar, Onur, et al.
Published: (2024)
Posterior Sampling-Based Bayesian Optimization with Tighter Bayesian Regret Bounds
by: Takeno, Shion, et al.
Published: (2023)
by: Takeno, Shion, et al.
Published: (2023)
Active learning for level set estimation under input uncertainty and its extensions
by: Inatsu, Yu, et al.
Published: (2019)
by: Inatsu, Yu, et al.
Published: (2019)
DomainLab: A modular Python package for domain generalization in deep learning
by: Sun, Xudong, et al.
Published: (2024)
by: Sun, Xudong, et al.
Published: (2024)
A Class Inference Scheme With Dempster-Shafer Theory for Learning Fuzzy-Classifier Systems
by: Shiraishi, Hiroki, et al.
Published: (2025)
by: Shiraishi, Hiroki, et al.
Published: (2025)
Portable Reward Tuning: Towards Reusable Fine-Tuning across Different Pretrained Models
by: Chijiwa, Daiki, et al.
Published: (2025)
by: Chijiwa, Daiki, et al.
Published: (2025)
FDApy: a Python package for functional data
by: Golovkine, Steven
Published: (2021)
by: Golovkine, Steven
Published: (2021)
bacpipe: a Python package to make bioacoustic deep learning models accessible
by: Kather, Vincent S., et al.
Published: (2026)
by: Kather, Vincent S., et al.
Published: (2026)
Deep Fast Machine Learning Utils: A Python Library for Streamlined Machine Learning Prototyping
by: Prezja, Fabi
Published: (2024)
by: Prezja, Fabi
Published: (2024)
Simulation-based Inference with the Python Package sbijax
by: Dirmeier, Simon, et al.
Published: (2024)
by: Dirmeier, Simon, et al.
Published: (2024)
maneuverRecognition -- A Python package for Timeseries Classification in the domain of Vehicle Telematics
by: Schuster, Jonathan, et al.
Published: (2025)
by: Schuster, Jonathan, et al.
Published: (2025)
FairLangProc: A Python package for fairness in NLP
by: Pérez-Peralta, Arturo, et al.
Published: (2025)
by: Pérez-Peralta, Arturo, et al.
Published: (2025)
EpiLearn: A Python Library for Machine Learning in Epidemic Modeling
by: Liu, Zewen, et al.
Published: (2024)
by: Liu, Zewen, et al.
Published: (2024)
TorchDA: A Python package for performing data assimilation with deep learning forward and transformation functions
by: Cheng, Sibo, et al.
Published: (2024)
by: Cheng, Sibo, et al.
Published: (2024)
Statistical Inference in Reinforcement Learning: A Selective Survey
by: Shi, Chengchun
Published: (2025)
by: Shi, Chengchun
Published: (2025)
Goodness-of-Fit and Clustering of Spherical Data: the QuadratiK package in R and Python
by: Saraceno, Giovanni, et al.
Published: (2024)
by: Saraceno, Giovanni, et al.
Published: (2024)
Similar Items
-
Statistical Test for Saliency Maps of Graph Neural Networks via Selective Inference
by: Nishino, Shuichi, et al.
Published: (2025) -
Post-ADC Inference: Valid Inference After Active Data Collection
by: Nishino, Shuichi, et al.
Published: (2026) -
Statistical Test for Auto Feature Engineering by Selective Inference
by: Matsukawa, Tatsuya, et al.
Published: (2024) -
Quantifying Statistical Significance of Deep Nearest Neighbor Anomaly Detection via Selective Inference
by: Niihori, Mizuki, et al.
Published: (2025) -
Statistical Test for Diffusion-Based Anomaly Localization via Selective Inference
by: Katsuoka, Teruyuki, et al.
Published: (2024)