Saved in:
| Main Authors: | Math, Hugo, Lienhart, Rainer |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2509.19112 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
One-Shot Multi-Label Causal Discovery in High-Dimensional Event Sequences
by: Math, Hugo, et al.
Published: (2025)
by: Math, Hugo, et al.
Published: (2025)
Scalable Sample-Level Causal Discovery in Event Sequences via Autoregressive Density Estimation
by: Math, Hugo, et al.
Published: (2026)
by: Math, Hugo, et al.
Published: (2026)
Learning to Predict, Discover, and Reason in High-Dimensional Event Sequences
by: Math, Hugo
Published: (2026)
by: Math, Hugo
Published: (2026)
Transforming Vehicle Diagnostics: A Multimodal Approach to Error Patterns Prediction
by: Math, Hugo, et al.
Published: (2026)
by: Math, Hugo, et al.
Published: (2026)
Multi-Agent Causal Reasoning System for Error Pattern Rule Automation in Vehicles
by: Math, Hugo, et al.
Published: (2026)
by: Math, Hugo, et al.
Published: (2026)
Harnessing Event Sensory Data for Error Pattern Prediction in Vehicles: A Language Model Approach
by: Math, Hugo, et al.
Published: (2024)
by: Math, Hugo, et al.
Published: (2024)
Towards Ball Spin and Trajectory Analysis in Table Tennis Broadcast Videos via Physically Grounded Synthetic-to-Real Transfer
by: Kienzle, Daniel, et al.
Published: (2025)
by: Kienzle, Daniel, et al.
Published: (2025)
CAOS: Conformal Aggregation of One-Shot Predictors
by: Waldron, Maja
Published: (2026)
by: Waldron, Maja
Published: (2026)
Segformer++: Efficient Token-Merging Strategies for High-Resolution Semantic Segmentation
by: Kienzle, Daniel, et al.
Published: (2024)
by: Kienzle, Daniel, et al.
Published: (2024)
CiliaGraph: Enabling Expression-enhanced Hyper-Dimensional Computation in Ultra-Lightweight and One-Shot Graph Classification on Edge
by: Han, Yuxi, et al.
Published: (2024)
by: Han, Yuxi, et al.
Published: (2024)
Multi-Domain Causal Discovery in Bijective Causal Models
by: Jalaldoust, Kasra, et al.
Published: (2025)
by: Jalaldoust, Kasra, et al.
Published: (2025)
Large Language Models are Effective Priors for Causal Graph Discovery
by: Darvariu, Victor-Alexandru, et al.
Published: (2024)
by: Darvariu, Victor-Alexandru, et al.
Published: (2024)
LGAN: An Efficient High-Order Graph Neural Network via the Line Graph Aggregation
by: Du, Lin, et al.
Published: (2025)
by: Du, Lin, et al.
Published: (2025)
Causal Discovery by Interventions via Integer Programming
by: Elrefaey, Abdelmonem, et al.
Published: (2024)
by: Elrefaey, Abdelmonem, et al.
Published: (2024)
EVIL: Evolving Interpretable Algorithms for Zero-Shot Inference on Event Sequences and Time Series with LLMs
by: Berghaus, David
Published: (2026)
by: Berghaus, David
Published: (2026)
Towards a Larger Model via One-Shot Federated Learning on Heterogeneous Client Models
by: Ye, Wenxuan, et al.
Published: (2025)
by: Ye, Wenxuan, et al.
Published: (2025)
Mask2Cause: Causal Discovery via Adjacency Constrained Causal Attention
by: Muhammad, Omar, et al.
Published: (2026)
by: Muhammad, Omar, et al.
Published: (2026)
Causal Time-Series Synchronization for Multi-Dimensional Forecasting
by: Mayr, Michael, et al.
Published: (2024)
by: Mayr, Michael, et al.
Published: (2024)
Efficient Causal Graph Discovery Using Large Language Models
by: Jiralerspong, Thomas, et al.
Published: (2024)
by: Jiralerspong, Thomas, et al.
Published: (2024)
Context-aware Graph Causality Inference for Few-Shot Molecular Property Prediction
by: Hoang, Van Thuy, et al.
Published: (2026)
by: Hoang, Van Thuy, et al.
Published: (2026)
Few-Shot Causal Representation Learning for Out-of-Distribution Generalization on Heterogeneous Graphs
by: Ding, Pengfei, et al.
Published: (2024)
by: Ding, Pengfei, et al.
Published: (2024)
Rethinking Dimensional Rationale in Graph Contrastive Learning from Causal Perspective
by: Ji, Qirui, et al.
Published: (2023)
by: Ji, Qirui, et al.
Published: (2023)
seq2cause: Sample- And Population-Level Causal Discovery from Event Sequences using Autoregressive Models
by: Math, Hugo
Published: (2026)
by: Math, Hugo
Published: (2026)
Beyond Isolated Clients: Integrating Graph-Based Embeddings into Event Sequence Models
by: Proshian, Harry, et al.
Published: (2026)
by: Proshian, Harry, et al.
Published: (2026)
Meaningful Causal Aggregation and Paradoxical Confounding
by: Zhu, Yuchen, et al.
Published: (2023)
by: Zhu, Yuchen, et al.
Published: (2023)
Ordering-based Causal Discovery via Generalized Score Matching
by: Vo, Vy, et al.
Published: (2026)
by: Vo, Vy, et al.
Published: (2026)
Step-by-Step Causality: Transparent Causal Discovery with Multi-Agent Tree-Query and Adversarial Confidence Estimation
by: Ding, Ziyi, et al.
Published: (2026)
by: Ding, Ziyi, et al.
Published: (2026)
Local Causal Discovery for Statistically Efficient Causal Inference
by: Schubert, Mátyás, et al.
Published: (2025)
by: Schubert, Mátyás, et al.
Published: (2025)
TNPAR: Topological Neural Poisson Auto-Regressive Model for Learning Granger Causal Structure from Event Sequences
by: Liu, Yuequn, et al.
Published: (2023)
by: Liu, Yuequn, et al.
Published: (2023)
Can LLMs Leverage Observational Data? Towards Data-Driven Causal Discovery with LLMs
by: Susanti, Yuni, et al.
Published: (2025)
by: Susanti, Yuni, et al.
Published: (2025)
Embedding-Aware Feature Discovery: Bridging Latent Representations and Interpretable Features in Event Sequences
by: Sakhno, Artem, et al.
Published: (2026)
by: Sakhno, Artem, et al.
Published: (2026)
A Roadmap Towards Improving Multi-Agent Reinforcement Learning With Causal Discovery And Inference
by: Briglia, Giovanni, et al.
Published: (2025)
by: Briglia, Giovanni, et al.
Published: (2025)
Causal Discovery from Poisson Branching Structural Causal Model Using High-Order Cumulant with Path Analysis
by: Qiao, Jie, et al.
Published: (2024)
by: Qiao, Jie, et al.
Published: (2024)
Efficient Differentiable Causal Discovery via Reliable Super-Structure Learning
by: Ma, Pingchuan, et al.
Published: (2026)
by: Ma, Pingchuan, et al.
Published: (2026)
Efficient Discovery of Approximate Causal Abstractions via Neural Mechanism Sparsification
by: Asiaee, Amir
Published: (2026)
by: Asiaee, Amir
Published: (2026)
Graph Neural Network Causal Explanation via Neural Causal Models
by: Behnam, Arman, et al.
Published: (2024)
by: Behnam, Arman, et al.
Published: (2024)
Graph-Mamba: Towards Long-Range Graph Sequence Modeling with Selective State Spaces
by: Wang, Chloe, et al.
Published: (2024)
by: Wang, Chloe, et al.
Published: (2024)
GRAIN: Multi-Granular and Implicit Information Aggregation Graph Neural Network for Heterophilous Graphs
by: Zhao, Songwei, et al.
Published: (2025)
by: Zhao, Songwei, et al.
Published: (2025)
Differentiable Constraint-Based Causal Discovery
by: Zhou, Jincheng, et al.
Published: (2025)
by: Zhou, Jincheng, et al.
Published: (2025)
Relational Causal Discovery with Latent Confounders
by: Negro, Matteo, et al.
Published: (2025)
by: Negro, Matteo, et al.
Published: (2025)
Similar Items
-
One-Shot Multi-Label Causal Discovery in High-Dimensional Event Sequences
by: Math, Hugo, et al.
Published: (2025) -
Scalable Sample-Level Causal Discovery in Event Sequences via Autoregressive Density Estimation
by: Math, Hugo, et al.
Published: (2026) -
Learning to Predict, Discover, and Reason in High-Dimensional Event Sequences
by: Math, Hugo
Published: (2026) -
Transforming Vehicle Diagnostics: A Multimodal Approach to Error Patterns Prediction
by: Math, Hugo, et al.
Published: (2026) -
Multi-Agent Causal Reasoning System for Error Pattern Rule Automation in Vehicles
by: Math, Hugo, et al.
Published: (2026)