Towards a Probabilistic Fusion Approach for Robust Battery Prognostics
Fuente:
arXiv
Saved in:
| Main Authors: | Alcibar, Jokin, Aizpurua, Jose I., Zugasti, Ekhi |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A Hybrid Probabilistic Battery Health Management Approach for Robust Inspection Drone Operations
by: Alcibar, Jokin, et al.
Published: (2024)
by: Alcibar, Jokin, et al.
Published: (2024)
Disentangling Aleatoric and Epistemic Uncertainty in Physics-Informed Neural Networks. Application to Insulation Material Degradation Prognostics
by: Ramirez, Ibai, et al.
Published: (2026)
by: Ramirez, Ibai, et al.
Published: (2026)
Bayesian Physics Informed Neural Networks for Reliable Transformer Prognostics
by: Ramirez, Ibai, et al.
Published: (2025)
by: Ramirez, Ibai, et al.
Published: (2025)
A Probabilistic Consensus-Driven Approach for Robust Counterfactual Explanations
by: Kostrzewa, Marcin, et al.
Published: (2026)
by: Kostrzewa, Marcin, et al.
Published: (2026)
Knowledge-Aware Modeling with Frequency Adaptive Learning for Battery Health Prognostics
by: Pamshetti, Vijay Babu, et al.
Published: (2025)
by: Pamshetti, Vijay Babu, et al.
Published: (2025)
Credibility-Aware Multi-Modal Fusion Using Probabilistic Circuits
by: Sidheekh, Sahil, et al.
Published: (2024)
by: Sidheekh, Sahil, et al.
Published: (2024)
Rigorous Probabilistic Guarantees for Robust Counterfactual Explanations
by: Marzari, Luca, et al.
Published: (2024)
by: Marzari, Luca, et al.
Published: (2024)
Counterfactual Explanations with Probabilistic Guarantees on their Robustness to Model Change
by: Stępka, Ignacy, et al.
Published: (2024)
by: Stępka, Ignacy, et al.
Published: (2024)
Understanding and Improving Adversarial Robustness of Neural Probabilistic Circuits
by: Chen, Weixin, et al.
Published: (2025)
by: Chen, Weixin, et al.
Published: (2025)
Robust Probabilistic Shielding for Safe Offline Reinforcement Learning
by: Galesloot, Maris F. L., et al.
Published: (2026)
by: Galesloot, Maris F. L., et al.
Published: (2026)
Towards Trustworthy Machine Learning in Production: An Overview of the Robustness in MLOps Approach
by: Bayram, Firas, et al.
Published: (2024)
by: Bayram, Firas, et al.
Published: (2024)
Tensor Networks for Explainable Machine Learning in Cybersecurity
by: Aizpurua, Borja, et al.
Published: (2023)
by: Aizpurua, Borja, et al.
Published: (2023)
AI-Driven Prognostics for State of Health Prediction in Li-ion Batteries: A Comprehensive Analysis with Validation
by: Ding, Tianqi, et al.
Published: (2025)
by: Ding, Tianqi, et al.
Published: (2025)
Towards Probabilistic Inductive Logic Programming with Neurosymbolic Inference and Relaxation
by: Hillerstrom, Fieke, et al.
Published: (2024)
by: Hillerstrom, Fieke, et al.
Published: (2024)
Probabilistic Token Alignment for Large Language Model Fusion
by: Zeng, Runjia, et al.
Published: (2025)
by: Zeng, Runjia, et al.
Published: (2025)
Towards Realistic Guarantees: A Probabilistic Certificate for SmoothLLM
by: Kumarappan, Adarsh, et al.
Published: (2025)
by: Kumarappan, Adarsh, et al.
Published: (2025)
The Probabilistic Tsetlin Machine: A Novel Approach to Uncertainty Quantification
by: Abeyrathna, K. Darshana, et al.
Published: (2024)
by: Abeyrathna, K. Darshana, et al.
Published: (2024)
HiTZ at VarDial 2025 NorSID: Overcoming Data Scarcity with Language Transfer and Automatic Data Annotation
by: Bengoetxea, Jaione, et al.
Published: (2024)
by: Bengoetxea, Jaione, et al.
Published: (2024)
Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting
by: Rasul, Kashif, et al.
Published: (2023)
by: Rasul, Kashif, et al.
Published: (2023)
COLEP: Certifiably Robust Learning-Reasoning Conformal Prediction via Probabilistic Circuits
by: Kang, Mintong, et al.
Published: (2024)
by: Kang, Mintong, et al.
Published: (2024)
When Smaller Wins: Dual-Stage Distillation and Pareto-Guided Compression of Liquid Neural Networks for Edge Battery Prognostics
by: Kannan, Dhivya Dharshini, et al.
Published: (2026)
by: Kannan, Dhivya Dharshini, et al.
Published: (2026)
Quantum Large Language Models via Tensor Network Disentanglers
by: Aizpurua, Borja, et al.
Published: (2024)
by: Aizpurua, Borja, et al.
Published: (2024)
Reinforcement Learning for Control with Probabilistic Stability Guarantee: A Finite-Sample Approach
by: Han, Minghao, et al.
Published: (2026)
by: Han, Minghao, et al.
Published: (2026)
Towards One Model for Classical Dimensionality Reduction: A Probabilistic Perspective on UMAP and t-SNE
by: Ravuri, Aditya, et al.
Published: (2024)
by: Ravuri, Aditya, et al.
Published: (2024)
Towards Explainable Fusion and Balanced Learning in Multimodal Sentiment Analysis
by: Luo, Miaosen, et al.
Published: (2025)
by: Luo, Miaosen, et al.
Published: (2025)
Are Transformers More Robust? Towards Exact Robustness Verification for Transformers
by: Liao, Brian Hsuan-Cheng, et al.
Published: (2022)
by: Liao, Brian Hsuan-Cheng, et al.
Published: (2022)
Data-Driven Lipschitz Continuity: A Cost-Effective Approach to Improve Adversarial Robustness
by: Chen, Erh-Chung, et al.
Published: (2024)
by: Chen, Erh-Chung, et al.
Published: (2024)
Bayesian Kolmogorov Arnold Networks (Bayesian_KANs): A Probabilistic Approach to Enhance Accuracy and Interpretability
by: Hassan, Masoud Muhammed
Published: (2024)
by: Hassan, Masoud Muhammed
Published: (2024)
Flexible Bivariate Beta Mixture Model: A Probabilistic Approach for Clustering Complex Data Structures
by: Hsu, Yung-Peng, et al.
Published: (2025)
by: Hsu, Yung-Peng, et al.
Published: (2025)
OrderFusion: Encoding Orderbook for End-to-End Probabilistic Intraday Electricity Price Forecasting
by: Yu, Runyao, et al.
Published: (2025)
by: Yu, Runyao, et al.
Published: (2025)
Towards Effective Fusion and Forecasting of Multimodal Spatio-temporal Data for Smart Mobility
by: Wang, Chenxing
Published: (2024)
by: Wang, Chenxing
Published: (2024)
Towards Adversarially Robust Deep Metric Learning
by: Ke, Xiaopeng
Published: (2025)
by: Ke, Xiaopeng
Published: (2025)
NSF-MAP: Neurosymbolic Multimodal Fusion for Robust and Interpretable Anomaly Prediction in Assembly Pipelines
by: Shyalika, Chathurangi, et al.
Published: (2025)
by: Shyalika, Chathurangi, et al.
Published: (2025)
Toward a Holistic Approach to Continual Model Merging
by: Phan, Hoang, et al.
Published: (2025)
by: Phan, Hoang, et al.
Published: (2025)
Towards Privacy-Preserving Relational Data Synthesis via Probabilistic Relational Models
by: Luttermann, Malte, et al.
Published: (2024)
by: Luttermann, Malte, et al.
Published: (2024)
Causal Diffusion Autoencoders: Toward Counterfactual Generation via Diffusion Probabilistic Models
by: Komanduri, Aneesh, et al.
Published: (2024)
by: Komanduri, Aneesh, et al.
Published: (2024)
Probabilistic Artificial Intelligence
by: Krause, Andreas, et al.
Published: (2025)
by: Krause, Andreas, et al.
Published: (2025)
Machine Learning Approaches for Diagnostics and Prognostics of Industrial Systems Using Open Source Data from PHM Data Challenges: A Review
by: Su, Hanqi, et al.
Published: (2023)
by: Su, Hanqi, et al.
Published: (2023)
Quantum-enhanced Large Language Models on Quantum Hardware via Cayley Unitary Adapters
by: Aizpurua, Borja, et al.
Published: (2026)
by: Aizpurua, Borja, et al.
Published: (2026)
Towards Efficient Pareto Set Approximation via Mixture of Experts Based Model Fusion
by: Tang, Anke, et al.
Published: (2024)
by: Tang, Anke, et al.
Published: (2024)
Similar Items
-
A Hybrid Probabilistic Battery Health Management Approach for Robust Inspection Drone Operations
by: Alcibar, Jokin, et al.
Published: (2024) -
Disentangling Aleatoric and Epistemic Uncertainty in Physics-Informed Neural Networks. Application to Insulation Material Degradation Prognostics
by: Ramirez, Ibai, et al.
Published: (2026) -
Bayesian Physics Informed Neural Networks for Reliable Transformer Prognostics
by: Ramirez, Ibai, et al.
Published: (2025) -
A Probabilistic Consensus-Driven Approach for Robust Counterfactual Explanations
by: Kostrzewa, Marcin, et al.
Published: (2026) -
Knowledge-Aware Modeling with Frequency Adaptive Learning for Battery Health Prognostics
by: Pamshetti, Vijay Babu, et al.
Published: (2025)