Beyond Coefficients: Forecast-Necessity Testing for Interpretable Causal Discovery in Nonlinear Time-Series Models
Fuente:
arXiv
Guardado en:
| Autores principales: | Kuskova, Valentina, Zaytsev, Dmitry, Coppedge, Michael |
|---|---|
| Formato: | Preprint |
| Publicado: |
2026
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Function-Valued Causal Influence in Nonlinear Time Series
por: Kuskova, Valentina V., et al.
Publicado: (2026)
por: Kuskova, Valentina V., et al.
Publicado: (2026)
Trajectory-Aware Reliability Modeling of Democratic Systems
por: Zaytsev, Dmitry, et al.
Publicado: (2026)
por: Zaytsev, Dmitry, et al.
Publicado: (2026)
From Causal Discovery to Dynamic Causal Inference in Neural Time Series
por: Zaytsev, Dmitry, et al.
Publicado: (2026)
por: Zaytsev, Dmitry, et al.
Publicado: (2026)
DecompKAN: Decomposed Patch-KAN for Long-Term Time Series Forecasting
por: Mysore, Naveen
Publicado: (2026)
por: Mysore, Naveen
Publicado: (2026)
Data-driven Circuit Discovery for Interpretability of Language Models
por: Rai, Daking, et al.
Publicado: (2026)
por: Rai, Daking, et al.
Publicado: (2026)
Improving Time Series Classification with Representation Soft Label Smoothing
por: Ma, Hengyi, et al.
Publicado: (2024)
por: Ma, Hengyi, et al.
Publicado: (2024)
From Features to Graphs: Exploring Graph Structures and Pairwise Interactions via GNNs
por: Yamchote, Phaphontee, et al.
Publicado: (2025)
por: Yamchote, Phaphontee, et al.
Publicado: (2025)
ProactBench: Beyond What The User Asked For
por: Harfi, Sepehr, et al.
Publicado: (2026)
por: Harfi, Sepehr, et al.
Publicado: (2026)
cPNN: Continuous Progressive Neural Networks for Evolving Streaming Time Series
por: Giannini, Federico, et al.
Publicado: (2026)
por: Giannini, Federico, et al.
Publicado: (2026)
Decentralized Time Series Classification with ROCKET Features
por: Casella, Bruno, et al.
Publicado: (2025)
por: Casella, Bruno, et al.
Publicado: (2025)
Interpretability Can Be Actionable
por: Orgad, Hadas, et al.
Publicado: (2026)
por: Orgad, Hadas, et al.
Publicado: (2026)
Position: Mechanistic Interpretability Must Disclose Identification Assumptions for Causal Claims
por: Lin, Zezheng, et al.
Publicado: (2026)
por: Lin, Zezheng, et al.
Publicado: (2026)
KAN vs LSTM Performance in Time Series Forecasting
por: Rather, Tabish Ali, et al.
Publicado: (2025)
por: Rather, Tabish Ali, et al.
Publicado: (2025)
Causal Dimensionality of Transformer Representations: Measurement, Scaling, and Layer Structure
por: Sarkar, Nilesh, et al.
Publicado: (2026)
por: Sarkar, Nilesh, et al.
Publicado: (2026)
AIPsy-Affect: A Keyword-Free Clinical Stimulus Battery for Mechanistic Interpretability of Emotion in Language Models
por: Keeman, Michael
Publicado: (2026)
por: Keeman, Michael
Publicado: (2026)
Agentic Discovery of Neural Architectures: AIRA-Compose and AIRA-Design
por: Pepe, Alberto, et al.
Publicado: (2026)
por: Pepe, Alberto, et al.
Publicado: (2026)
Communications to Circulations: Real-Time 3D Wind Field Prediction Using 5G GNSS Signals and Deep Learning
por: Ye, Yuchen, et al.
Publicado: (2025)
por: Ye, Yuchen, et al.
Publicado: (2025)
Alternative positional encoding functions for neural transformers
por: Lopez-Rubio, Ezequiel, et al.
Publicado: (2025)
por: Lopez-Rubio, Ezequiel, et al.
Publicado: (2025)
The Origins of Representation Manifolds in Large Language Models
por: Modell, Alexander, et al.
Publicado: (2025)
por: Modell, Alexander, et al.
Publicado: (2025)
HGTUL: A Hypergraph-based Model For Trajectory User Linking
por: Chang, Fengjie, et al.
Publicado: (2025)
por: Chang, Fengjie, et al.
Publicado: (2025)
On Privacy Leakage in Tabular Diffusion Models: Influential Factors, Attacker Knowledge, and Metrics
por: Shafieinejad, Masoumeh, et al.
Publicado: (2026)
por: Shafieinejad, Masoumeh, et al.
Publicado: (2026)
How Pruning Reshapes Features: Sparse Autoencoder Analysis of Weight-Pruned Language Models
por: Borobia, Hector, et al.
Publicado: (2026)
por: Borobia, Hector, et al.
Publicado: (2026)
ExpliCa: Evaluating Explicit Causal Reasoning in Large Language Models
por: Miliani, Martina, et al.
Publicado: (2025)
por: Miliani, Martina, et al.
Publicado: (2025)
Static Seeding and Clustering of LSTM Embeddings to Learn from Loosely Time-Decoupled Events
por: Manasseh, Christian, et al.
Publicado: (2022)
por: Manasseh, Christian, et al.
Publicado: (2022)
Can Agentic AI Match the Performance of Human Data Scientists?
por: Luo, An, et al.
Publicado: (2025)
por: Luo, An, et al.
Publicado: (2025)
AgentDS Technical Report: Benchmarking the Future of Human-AI Collaboration in Domain-Specific Data Science
por: Luo, An, et al.
Publicado: (2026)
por: Luo, An, et al.
Publicado: (2026)
Scalable Heterogeneous Graph Foundation Models for Data-Driven Optimal Power Flow in Smart Grids
por: Pasini, Massimiliano Lupo, et al.
Publicado: (2026)
por: Pasini, Massimiliano Lupo, et al.
Publicado: (2026)
Contextual Representation Anchor Network to Alleviate Selection Bias in Few-Shot Drug Discovery
por: Li, Ruifeng, et al.
Publicado: (2024)
por: Li, Ruifeng, et al.
Publicado: (2024)
Deep Learning-Based Forecasting of Boarding Patient Counts to Address ED Overcrowding
por: Vural, Orhun, et al.
Publicado: (2025)
por: Vural, Orhun, et al.
Publicado: (2025)
Neural Concept Verifier: Scaling Prover-Verifier Games via Concept Encodings
por: Turan, Berkant, et al.
Publicado: (2025)
por: Turan, Berkant, et al.
Publicado: (2025)
Causal Direction from Convergence Time: Faster Training in the True Causal Direction
por: Tamim, Abdulrahman
Publicado: (2026)
por: Tamim, Abdulrahman
Publicado: (2026)
FedUNet: A Lightweight Additive U-Net Module for Federated Learning with Heterogeneous Models
por: Seo, Beomseok, et al.
Publicado: (2025)
por: Seo, Beomseok, et al.
Publicado: (2025)
Lost or Hidden? A Concept-Level Forgetting in Supervised Continual Learning
por: Filus, Katarzyna, et al.
Publicado: (2026)
por: Filus, Katarzyna, et al.
Publicado: (2026)
Scaling Laws in the Tiny Regime: How Small Models Change Their Mistakes
por: Alnemari, Mohammed, et al.
Publicado: (2026)
por: Alnemari, Mohammed, et al.
Publicado: (2026)
Model-Free Local Recalibration of Neural Networks
por: Torres, R., et al.
Publicado: (2024)
por: Torres, R., et al.
Publicado: (2024)
RG-TTA: Regime-Guided Meta-Control for Test-Time Adaptation in Streaming Time Series
por: Kumar, Indar, et al.
Publicado: (2026)
por: Kumar, Indar, et al.
Publicado: (2026)
Conditional Temporal Neural Processes with Covariance Loss
por: Yoo, Boseon, et al.
Publicado: (2025)
por: Yoo, Boseon, et al.
Publicado: (2025)
DNNShifter: An Efficient DNN Pruning System for Edge Computing
por: Eccles, Bailey J., et al.
Publicado: (2023)
por: Eccles, Bailey J., et al.
Publicado: (2023)
Reliable Unlearning Harmful Information in LLMs with Metamorphosis Representation Projection
por: Wu, Chengcan, et al.
Publicado: (2025)
por: Wu, Chengcan, et al.
Publicado: (2025)
Tazza: Shuffling Neural Network Parameters for Secure and Private Federated Learning
por: Lee, Kichang, et al.
Publicado: (2024)
por: Lee, Kichang, et al.
Publicado: (2024)
Ejemplares similares
-
Function-Valued Causal Influence in Nonlinear Time Series
por: Kuskova, Valentina V., et al.
Publicado: (2026) -
Trajectory-Aware Reliability Modeling of Democratic Systems
por: Zaytsev, Dmitry, et al.
Publicado: (2026) -
From Causal Discovery to Dynamic Causal Inference in Neural Time Series
por: Zaytsev, Dmitry, et al.
Publicado: (2026) -
DecompKAN: Decomposed Patch-KAN for Long-Term Time Series Forecasting
por: Mysore, Naveen
Publicado: (2026) -
Data-driven Circuit Discovery for Interpretability of Language Models
por: Rai, Daking, et al.
Publicado: (2026)