:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Fan, Shicheng, Elhendawy, Nour, Sun, Jianle, Fang, Ke, Zhang, Kun, Wang, Yihang, Cheng, Lu
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence
Online Access:	https://arxiv.org/abs/2605.05524
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

TRACE: Trajectory Recovery for Continuous Mechanism Evolution in Causal Representation Learning
by: Fan, Shicheng, et al.
Published: (2026)

Causal Discovery for Irregularly Time Series with Consistency Guarantees
by: Li, Weihong, et al.
Published: (2025)

Dynamic Sparse Causal-Attention Temporal Networks for Interpretable Causality Discovery in Multivariate Time Series
by: Zerkouk, Meriem, et al.
Published: (2025)

Interpretable Scientific Discovery with Symbolic Regression: A Review
by: Makke, Nour, et al.
Published: (2022)

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data
by: Cheng, Debo, et al.
Published: (2024)

Causal Discovery in Semi-Stationary Time Series
by: Gao, Shanyun, et al.
Published: (2024)

CausalCompass: Evaluating the Robustness of Time-Series Causal Discovery in Misspecified Scenarios
by: Yi, Huiyang, et al.
Published: (2026)

From Causal Discovery to Dynamic Causal Inference in Neural Time Series
by: Zaytsev, Dmitry, et al.
Published: (2026)

Intervention-Based Time Series Causal Discovery via Simulator-Generated Interventional Distributions
by: Okita, Tsuyoshi
Published: (2026)

Shylock: Causal Discovery in Multivariate Time Series based on Hybrid Constraints
by: Li, Shuo, et al.
Published: (2025)

Nonparametric Identification and Inference for Counterfactual Distributions with Confounding
by: Sun, Jianle, et al.
Published: (2026)

When Selection Meets Intervention: Additional Complexities in Causal Discovery
by: Dai, Haoyue, et al.
Published: (2025)

Causal Discovery-Driven Change Point Detection in Time Series
by: Gao, Shanyun, et al.
Published: (2024)

TimeCapsule: Solving the Jigsaw Puzzle of Long-Term Time Series Forecasting with Compressed Predictive Representations
by: Lu, Yihang, et al.
Published: (2025)

SciTS: Scientific Time Series Understanding and Generation with LLMs
by: Wu, Wen, et al.
Published: (2025)

Explaining Time Series via Contrastive and Locally Sparse Perturbations
by: Liu, Zichuan, et al.
Published: (2024)

Identifying Selections for Unsupervised Subtask Discovery
by: Qiu, Yiwen, et al.
Published: (2024)

Accurate and Efficient Multi-Channel Time Series Forecasting via Sparse Attention Mechanism
by: Gao, Lei, et al.
Published: (2026)

A Survey on Causal Discovery Methods for I.I.D. and Time Series Data
by: Hasan, Uzma, et al.
Published: (2023)

CAnDOIT: Causal Discovery with Observational and Interventional Data from Time-Series
by: Castri, Luca, et al.
Published: (2024)

Robust Time Series Causal Discovery for Agent-Based Model Validation
by: Yu, Gene, et al.
Published: (2024)

MOSAIC: Masked Objective with Selective Adaptation for In-domain Contrastive Learning
by: Pavlova, Vera, et al.
Published: (2025)

Causal Discovery from Time Series with Hybrids of Constraint-Based and Noise-Based Algorithms
by: Bystrova, Daria, et al.
Published: (2023)

Time Series Domain Adaptation via Latent Invariant Causal Mechanism
by: Cai, Ruichu, et al.
Published: (2025)

VCDF: A Validated Consensus-Driven Framework for Time Series Causal Discovery
by: Yu, Gene, et al.
Published: (2026)

TimeChat: A Time-sensitive Multimodal Large Language Model for Long Video Understanding
by: Ren, Shuhuai, et al.
Published: (2023)

Diagnosing and Repairing Unsafe Channels in Vision-Language Models via Causal Discovery and Dual-Modal Safety Subspace Projection
by: Fu, Jinhu, et al.
Published: (2026)

Mathematical Reasoning via Intervention-Based Time-Series Causal Discovery Using LLMs as Concept Mastery Simulators
by: Okita, Tsuyoshi
Published: (2026)

Fourier Basis Mapping: A Time-Frequency Learning Framework for Time Series Forecasting
by: Yang, Runze, et al.
Published: (2025)

Efficient Ensemble Conditional Independence Test Framework for Causal Discovery
by: Guan, Zhengkang, et al.
Published: (2025)

Effective Causal Discovery under Identifiable Heteroscedastic Noise Model
by: Yin, Naiyu, et al.
Published: (2023)

Causal Language Control in Multilingual Transformers via Sparse Feature Steering
by: Chou, Cheng-Ting, et al.
Published: (2025)

Learning from Sparse Offline Datasets via Conservative Density Estimation
by: Cen, Zhepeng, et al.
Published: (2024)

Deep Frequency Derivative Learning for Non-stationary Time Series Forecasting
by: Fan, Wei, et al.
Published: (2024)

Causal Ordering for Structure Learning from Time Series
by: Sanchez, Pedro P., et al.
Published: (2025)

KairosAgent: Agentic Time Series Forecasting with Fused Semantic Reasoning
by: Feng, Kun, et al.
Published: (2026)

LOCAL: Learning with Orientation Matrix to Infer Causal Structure from Time Series Data
by: Zhang, Jiajun, et al.
Published: (2024)

TTCD:Transformer Integrated Temporal Causal Discovery from Non-Stationary Time Series Data
by: Faruque, Omar, et al.
Published: (2026)

MOSAIC: Composable Safety Alignment with Modular Control Tokens
by: Peng, Jingyu, et al.
Published: (2026)

Dissecting Chronos: Sparse Autoencoders Reveal Causal Feature Hierarchies in Time Series Foundation Models
by: Mishra, Anurag
Published: (2026)