Explaining deep neural network models for electricity price forecasting with XAI
Fuente:
arXiv
Saved in:
| Main Authors: | Pesenti, Antoine, OSullivan, Aidan |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Grey-informed neural network for time-series forecasting
by: Xie, Wanli, et al.
Published: (2024)
by: Xie, Wanli, et al.
Published: (2024)
Distill n' Explain: explaining graph neural networks using simple surrogates
by: Pereira, Tamara, et al.
Published: (2023)
by: Pereira, Tamara, et al.
Published: (2023)
Utilizing Lyapunov Exponents in designing deep neural networks
by: Mittra, Tirthankar
Published: (2024)
by: Mittra, Tirthankar
Published: (2024)
Comparison of different Artificial Neural Networks for Bitcoin price forecasting
by: Baumann, Silas, et al.
Published: (2024)
by: Baumann, Silas, et al.
Published: (2024)
RDI: An adversarial robustness evaluation metric for deep neural networks based on model statistical features
by: Song, Jialei, et al.
Published: (2025)
by: Song, Jialei, et al.
Published: (2025)
Topological derivative approach for deep neural network architecture adaptation
by: Krishnanunni, C G, et al.
Published: (2025)
by: Krishnanunni, C G, et al.
Published: (2025)
Do deep neural networks utilize the weight space efficiently?
by: Koyun, Onur Can, et al.
Published: (2024)
by: Koyun, Onur Can, et al.
Published: (2024)
Delta-XAI: A Unified Framework for Explaining Prediction Changes in Online Time Series Monitoring
by: Kim, Changhun, et al.
Published: (2025)
by: Kim, Changhun, et al.
Published: (2025)
Stacking-based deep neural network for player scouting in football 1
by: Lacan, Simon
Published: (2024)
by: Lacan, Simon
Published: (2024)
LLMs for XAI: Future Directions for Explaining Explanations
by: Zytek, Alexandra, et al.
Published: (2024)
by: Zytek, Alexandra, et al.
Published: (2024)
Making deep neural networks right for the right scientific reasons by interacting with their explanations
by: Schramowski, Patrick, et al.
Published: (2020)
by: Schramowski, Patrick, et al.
Published: (2020)
Extreme value forecasting using relevance-based data augmentation with deep learning models
by: Hua, Junru, et al.
Published: (2025)
by: Hua, Junru, et al.
Published: (2025)
Can neural networks do arithmetic? A survey on the elementary numerical skills of state-of-the-art deep learning models
by: Testolin, Alberto
Published: (2023)
by: Testolin, Alberto
Published: (2023)
From paintbrush to pixel: A review of deep neural networks in AI-generated art
by: Maerten, Anne-Sofie, et al.
Published: (2023)
by: Maerten, Anne-Sofie, et al.
Published: (2023)
Short-term electricity load forecasting with multi-frequency reconstruction diffusion
by: Dong, Qi, et al.
Published: (2026)
by: Dong, Qi, et al.
Published: (2026)
Self-adaptive weights based on balanced residual decay rate for physics-informed neural networks and deep operator networks
by: Chen, Wenqian, et al.
Published: (2024)
by: Chen, Wenqian, et al.
Published: (2024)
Adaptive tumor growth forecasting via neural & universal ODEs
by: Subramanian, Kavya, et al.
Published: (2025)
by: Subramanian, Kavya, et al.
Published: (2025)
On-line conformalized neural networks ensembles for probabilistic forecasting of day-ahead electricity prices
by: Brusaferri, Alessandro, et al.
Published: (2024)
by: Brusaferri, Alessandro, et al.
Published: (2024)
Variational autoencoder-based neural network model compression
by: Cheng, Liang, et al.
Published: (2024)
by: Cheng, Liang, et al.
Published: (2024)
Scaling transformer neural networks for skillful and reliable medium-range weather forecasting
by: Nguyen, Tung, et al.
Published: (2023)
by: Nguyen, Tung, et al.
Published: (2023)
Recursive deep learning framework for forecasting the decadal world economic outlook
by: Wang, Tianyi, et al.
Published: (2023)
by: Wang, Tianyi, et al.
Published: (2023)
Exploring the design space of deep-learning-based weather forecasting systems
by: Siddiqui, Shoaib Ahmed, et al.
Published: (2024)
by: Siddiqui, Shoaib Ahmed, et al.
Published: (2024)
Sparsity in neural networks can improve their privacy
by: Gonon, Antoine, et al.
Published: (2023)
by: Gonon, Antoine, et al.
Published: (2023)
Short-term wind speed forecasting model based on an attention-gated recurrent neural network and error correction strategy
by: Huang, Haojian
Published: (2024)
by: Huang, Haojian
Published: (2024)
An algorithmic framework for the optimization of deep neural networks architectures and hyperparameters
by: Keisler, Julie, et al.
Published: (2023)
by: Keisler, Julie, et al.
Published: (2023)
Ultra-short-term solar power forecasting by deep learning and data reconstruction
by: Wang, Jinbao, et al.
Published: (2025)
by: Wang, Jinbao, et al.
Published: (2025)
A multiobjective continuation method to compute the regularization path of deep neural networks
by: Amakor, Augustina C., et al.
Published: (2023)
by: Amakor, Augustina C., et al.
Published: (2023)
PINNet: a deep neural network with pathway prior knowledge for Alzheimer's disease
by: Kim, Yeojin, et al.
Published: (2022)
by: Kim, Yeojin, et al.
Published: (2022)
Development of a graph neural network surrogate for travel demand modelling
by: Makarov, Nikita, et al.
Published: (2024)
by: Makarov, Nikita, et al.
Published: (2024)
Parallel BiLSTM-Transformer networks for forecasting chaotic dynamics
by: Ma, Junwen, et al.
Published: (2025)
by: Ma, Junwen, et al.
Published: (2025)
Comparative analysis of neural network architectures for short-term FOREX forecasting
by: Zafeiriou, Theodoros, et al.
Published: (2024)
by: Zafeiriou, Theodoros, et al.
Published: (2024)
Sobolev acceleration for neural networks
by: Oh, Jong Kwon, et al.
Published: (2025)
by: Oh, Jong Kwon, et al.
Published: (2025)
On permutation-invariant neural networks
by: Kimura, Masanari, et al.
Published: (2024)
by: Kimura, Masanari, et al.
Published: (2024)
Attention mechanisms in neural networks
by: Hays, Hasi
Published: (2026)
by: Hays, Hasi
Published: (2026)
A comparative study of deep learning and ensemble learning to extend the horizon of traffic forecasting
by: Zheng, Xiao, et al.
Published: (2025)
by: Zheng, Xiao, et al.
Published: (2025)
Efficient and provably convergent end-to-end training of deep neural networks with linear constraints
by: Yang, Zonglin, et al.
Published: (2026)
by: Yang, Zonglin, et al.
Published: (2026)
A Mechanistic Explanatory Strategy for XAI
by: Rabiza, Marcin
Published: (2024)
by: Rabiza, Marcin
Published: (2024)
Linearity-based neural network compression
by: Dobler, Silas, et al.
Published: (2025)
by: Dobler, Silas, et al.
Published: (2025)
Principles of Lipschitz continuity in neural networks
by: Luo, Róisín
Published: (2026)
by: Luo, Róisín
Published: (2026)
Integrating Bayesian methods with neural network--based model predictive control: a review
by: Karacelik, Asli
Published: (2025)
by: Karacelik, Asli
Published: (2025)
Similar Items
-
Grey-informed neural network for time-series forecasting
by: Xie, Wanli, et al.
Published: (2024) -
Distill n' Explain: explaining graph neural networks using simple surrogates
by: Pereira, Tamara, et al.
Published: (2023) -
Utilizing Lyapunov Exponents in designing deep neural networks
by: Mittra, Tirthankar
Published: (2024) -
Comparison of different Artificial Neural Networks for Bitcoin price forecasting
by: Baumann, Silas, et al.
Published: (2024) -
RDI: An adversarial robustness evaluation metric for deep neural networks based on model statistical features
by: Song, Jialei, et al.
Published: (2025)