Saved in:
| Main Authors: | Zimmer, Christoph, Meister, Mona, Nguyen-Tuong, Duy |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2402.06276 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Batch Active Learning in Gaussian Process Regression using Derivatives
by: Yu, Hon Sum Alec, et al.
Published: (2024)
by: Yu, Hon Sum Alec, et al.
Published: (2024)
Safe Active Learning for Gaussian Differential Equations
by: Glass, Leon, et al.
Published: (2024)
by: Glass, Leon, et al.
Published: (2024)
Future Aware Safe Active Learning of Time Varying Systems using Gaussian Processes
by: Lange-Hegermann, Markus, et al.
Published: (2024)
by: Lange-Hegermann, Markus, et al.
Published: (2024)
Efficiently Computable Safety Bounds for Gaussian Processes in Active Learning
by: Tebbe, Jörn, et al.
Published: (2024)
by: Tebbe, Jörn, et al.
Published: (2024)
Amortized Safe Active Learning for Real-Time Data Acquisition: Pretrained Neural Policies From Simulated Nonparametric Functions
by: Li, Cen-You, et al.
Published: (2025)
by: Li, Cen-You, et al.
Published: (2025)
Active Learning for Multiple Change Point Detection in Non-stationary Time Series with Deep Gaussian Processes
by: Zhao, Hao, et al.
Published: (2025)
by: Zhao, Hao, et al.
Published: (2025)
Improving Time Series Encoding with Noise-Aware Self-Supervised Learning and an Efficient Encoder
by: Nguyen, Duy A., et al.
Published: (2023)
by: Nguyen, Duy A., et al.
Published: (2023)
Self-Supervised Learning via Flow-Guided Neural Operator on Time-Series Data
by: Nguyen, Duy, et al.
Published: (2026)
by: Nguyen, Duy, et al.
Published: (2026)
Amortized Active Learning for Nonparametric Functions
by: Li, Cen-You, et al.
Published: (2024)
by: Li, Cen-You, et al.
Published: (2024)
Global Safe Sequential Learning via Efficient Knowledge Transfer
by: Li, Cen-You, et al.
Published: (2024)
by: Li, Cen-You, et al.
Published: (2024)
Persistent Homology-induced Graph Ensembles for Time Series Regressions
by: Nguyen, Viet The, et al.
Published: (2025)
by: Nguyen, Viet The, et al.
Published: (2025)
Robust Transfer Learning for Active Level Set Estimation with Locally Adaptive Gaussian Process Prior
by: Ngo, Giang, et al.
Published: (2024)
by: Ngo, Giang, et al.
Published: (2024)
Active Learning with Weak Supervision for Gaussian Processes
by: Olmin, Amanda, et al.
Published: (2022)
by: Olmin, Amanda, et al.
Published: (2022)
Gaussian Process Latent Variable Modeling for Few-shot Time Series Forecasting
by: Cheng, Yunyao, et al.
Published: (2022)
by: Cheng, Yunyao, et al.
Published: (2022)
Revisiting Kernel Attention with Correlated Gaussian Process Representation
by: Bui, Long Minh, et al.
Published: (2025)
by: Bui, Long Minh, et al.
Published: (2025)
Distributionally Robust Active Learning for Gaussian Process Regression
by: Takeno, Shion, et al.
Published: (2025)
by: Takeno, Shion, et al.
Published: (2025)
Generative Modeling of Approximately Periodic Time Series by a Posterior-Weighted Gaussian Process
by: Reich, Elias, et al.
Published: (2026)
by: Reich, Elias, et al.
Published: (2026)
On Almost Surely Safe Alignment of Large Language Models at Inference-Time
by: Ji, Xiaotong, et al.
Published: (2025)
by: Ji, Xiaotong, et al.
Published: (2025)
Tailored Architectures for Time Series Forecasting: Evaluating Deep Learning Models on Gaussian Process-Generated Data
by: Hankemeier, Victoria, et al.
Published: (2025)
by: Hankemeier, Victoria, et al.
Published: (2025)
Safe Time-Varying Optimization based on Gaussian Processes with Spatio-Temporal Kernel
by: Li, Jialin, et al.
Published: (2024)
by: Li, Jialin, et al.
Published: (2024)
Generating Synthetic Satellite Imagery With Deep-Learning Text-to-Image Models -- Technical Challenges and Implications for Monitoring and Verification
by: Nguyen, Tuong Vy, et al.
Published: (2024)
by: Nguyen, Tuong Vy, et al.
Published: (2024)
Active Learning for Manifold Gaussian Process Regression
by: Cheng, Yuanxing, et al.
Published: (2025)
by: Cheng, Yuanxing, et al.
Published: (2025)
Safe Reinforcement Learning via Recovery-based Shielding with Gaussian Process Dynamics Models
by: Goodall, Alexander W., et al.
Published: (2026)
by: Goodall, Alexander W., et al.
Published: (2026)
Physics-informed Gaussian Processes for Safe Envelope Expansion
by: Harp, D. Isaiah, et al.
Published: (2025)
by: Harp, D. Isaiah, et al.
Published: (2025)
Rethinking Large Language Model Distillation: A Constrained Markov Decision Process Perspective
by: Zimmer, Matthieu, et al.
Published: (2025)
by: Zimmer, Matthieu, et al.
Published: (2025)
Learning to Forget: Bayesian Time Series Forecasting using Recurrent Sparse Spectrum Signature Gaussian Processes
by: Tóth, Csaba, et al.
Published: (2024)
by: Tóth, Csaba, et al.
Published: (2024)
Conformalised data synthesis
by: Meister, Julia A., et al.
Published: (2023)
by: Meister, Julia A., et al.
Published: (2023)
Time Series Gaussian Chain Graph Models
by: Fang, Qin, et al.
Published: (2026)
by: Fang, Qin, et al.
Published: (2026)
MGPATH: Vision-Language Model with Multi-Granular Prompt Learning for Few-Shot WSI Classification
by: Nguyen, Anh-Tien, et al.
Published: (2025)
by: Nguyen, Anh-Tien, et al.
Published: (2025)
Flow Matching with Gaussian Process Priors for Probabilistic Time Series Forecasting
by: Kollovieh, Marcel, et al.
Published: (2024)
by: Kollovieh, Marcel, et al.
Published: (2024)
Motion Code: Robust Time Series Classification and Forecasting via Sparse Variational Multi-Stochastic Processes Learning
by: Bajaj, Chandrajit, et al.
Published: (2024)
by: Bajaj, Chandrajit, et al.
Published: (2024)
Active Learning of Piecewise Gaussian Process Surrogates
by: Park, Chiwoo, et al.
Published: (2023)
by: Park, Chiwoo, et al.
Published: (2023)
Fake Advertisements Detection Using Automated Multimodal Learning: A Case Study for Vietnamese Real Estate Data
by: Nguyen, Duy, et al.
Published: (2025)
by: Nguyen, Duy, et al.
Published: (2025)
Empirical Comparison of Lightweight Forecasting Models for Seasonal and Non-Seasonal Time Series
by: Nguyen, Thanh Son, et al.
Published: (2025)
by: Nguyen, Thanh Son, et al.
Published: (2025)
Deep Intrinsic Coregionalization Multi-Output Gaussian Process Surrogate with Active Learning
by: Chang, Chun-Yi, et al.
Published: (2025)
by: Chang, Chun-Yi, et al.
Published: (2025)
Causality-Inspired Safe Residual Correction for Multivariate Time Series
by: Xie, Jianxiang, et al.
Published: (2025)
by: Xie, Jianxiang, et al.
Published: (2025)
Active Learning and Transfer Learning for Anomaly Detection in Time-Series Data
by: Kelleher, John D., et al.
Published: (2025)
by: Kelleher, John D., et al.
Published: (2025)
Active Learning for Derivative-Based Global Sensitivity Analysis with Gaussian Processes
by: Belakaria, Syrine, et al.
Published: (2024)
by: Belakaria, Syrine, et al.
Published: (2024)
Does Continued Pretraining on a Learner Corpus Improve Automated Essay Scoring on English Proficiency Tests? Evidence from EFCAMDAT
by: Nguyen, Duy Anh
Published: (2026)
by: Nguyen, Duy Anh
Published: (2026)
Sparse Model Soups: A Recipe for Improved Pruning via Model Averaging
by: Zimmer, Max, et al.
Published: (2023)
by: Zimmer, Max, et al.
Published: (2023)
Similar Items
-
Batch Active Learning in Gaussian Process Regression using Derivatives
by: Yu, Hon Sum Alec, et al.
Published: (2024) -
Safe Active Learning for Gaussian Differential Equations
by: Glass, Leon, et al.
Published: (2024) -
Future Aware Safe Active Learning of Time Varying Systems using Gaussian Processes
by: Lange-Hegermann, Markus, et al.
Published: (2024) -
Efficiently Computable Safety Bounds for Gaussian Processes in Active Learning
by: Tebbe, Jörn, et al.
Published: (2024) -
Amortized Safe Active Learning for Real-Time Data Acquisition: Pretrained Neural Policies From Simulated Nonparametric Functions
by: Li, Cen-You, et al.
Published: (2025)