Saved in:
| Main Authors: | Lei, Ming, Wu, Shufan, Baehr, Christophe |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2603.12305 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A Geometrically-Grounded Drive for MDL-Based Optimization in Deep Learning
by: Lei, Ming, et al.
Published: (2026)
by: Lei, Ming, et al.
Published: (2026)
A Comparative Theoretical Analysis of Entropy Control Methods in Reinforcement Learning
by: Lei, Ming, et al.
Published: (2026)
by: Lei, Ming, et al.
Published: (2026)
Geometric Meta-Learning via Coupled Ricci Flow: Unifying Knowledge Representation and Quantum Entanglement
by: Lei, Ming, et al.
Published: (2025)
by: Lei, Ming, et al.
Published: (2025)
A Full DAG Score-Based Algorithm for Learning Causal Bayesian Networks with Latent Confounders
by: Gonzales, Christophe, et al.
Published: (2024)
by: Gonzales, Christophe, et al.
Published: (2024)
Understanding Hardness of Vision-Language Compositionality from A Token-level Causal Lens
by: Chen, Ziliang, et al.
Published: (2025)
by: Chen, Ziliang, et al.
Published: (2025)
Estimating Causal Effects from Learned Causal Networks
by: Raichev, Anna, et al.
Published: (2024)
by: Raichev, Anna, et al.
Published: (2024)
EEG-DCNet: A Fast and Accurate MI-EEG Dilated CNN Classification Method
by: Peng, Wei, et al.
Published: (2024)
by: Peng, Wei, et al.
Published: (2024)
Neurocircuitry-Inspired Hierarchical Graph Causal Attention Networks for Explainable Depression Identification
by: Chen, Weidao, et al.
Published: (2025)
by: Chen, Weidao, et al.
Published: (2025)
Towards the Reusability and Compositionality of Causal Representations
by: Talon, Davide, et al.
Published: (2024)
by: Talon, Davide, et al.
Published: (2024)
Linear-Time Primitives for Algorithm Development in Graphical Causal Inference
by: Wienöbst, Marcel, et al.
Published: (2025)
by: Wienöbst, Marcel, et al.
Published: (2025)
CHLU: The Causal Hamiltonian Learning Unit as a Symplectic Primitive for Deep Learning
by: Jawahar, Pratik, et al.
Published: (2026)
by: Jawahar, Pratik, et al.
Published: (2026)
Towards Understanding Extrapolation: a Causal Lens
by: Kong, Lingjing, et al.
Published: (2025)
by: Kong, Lingjing, et al.
Published: (2025)
Graph Neural Network Causal Explanation via Neural Causal Models
by: Behnam, Arman, et al.
Published: (2024)
by: Behnam, Arman, et al.
Published: (2024)
Compositional Models for Estimating Causal Effects
by: Pruthi, Purva, et al.
Published: (2024)
by: Pruthi, Purva, et al.
Published: (2024)
Fine-Grained Causal Dynamics Learning with Quantization for Improving Robustness in Reinforcement Learning
by: Hwang, Inwoo, et al.
Published: (2024)
by: Hwang, Inwoo, et al.
Published: (2024)
From Identifiable Causal Representations to Controllable Counterfactual Generation: A Survey on Causal Generative Modeling
by: Komanduri, Aneesh, et al.
Published: (2023)
by: Komanduri, Aneesh, et al.
Published: (2023)
Logic Synthesis Optimization with Predictive Self-Supervision via Causal Transformers
by: Karimi, Raika, et al.
Published: (2024)
by: Karimi, Raika, et al.
Published: (2024)
Dynamic Sparse Causal-Attention Temporal Networks for Interpretable Causality Discovery in Multivariate Time Series
by: Zerkouk, Meriem, et al.
Published: (2025)
by: Zerkouk, Meriem, et al.
Published: (2025)
CausalMed: Causality-Based Personalized Medication Recommendation Centered on Patient health state
by: Li, Xiang, et al.
Published: (2024)
by: Li, Xiang, et al.
Published: (2024)
Hierarchical Causal Abduction: A Foundation Framework for Explainable Model Predictive Control
by: Naagarajan, Ramesh Arvind, et al.
Published: (2026)
by: Naagarajan, Ramesh Arvind, et al.
Published: (2026)
Causal Label Recovery in Payment Networks
by: Dhama, Gaurav
Published: (2026)
by: Dhama, Gaurav
Published: (2026)
Causal Graph Neural Networks for Healthcare
by: Mesinovic, Munib, et al.
Published: (2025)
by: Mesinovic, Munib, et al.
Published: (2025)
Intervention and Conditioning in Causal Bayesian Networks
by: Galhotra, Sainyam, et al.
Published: (2024)
by: Galhotra, Sainyam, et al.
Published: (2024)
Causal Discovery for Irregularly Time Series with Consistency Guarantees
by: Li, Weihong, et al.
Published: (2025)
by: Li, Weihong, et al.
Published: (2025)
Systems with Switching Causal Relations: A Meta-Causal Perspective
by: Willig, Moritz, et al.
Published: (2024)
by: Willig, Moritz, et al.
Published: (2024)
Individual Causal Inference with Structural Causal Model
by: Chang, Daniel T.
Published: (2025)
by: Chang, Daniel T.
Published: (2025)
Compositional Causal Reasoning Evaluation in Language Models
by: Maasch, Jacqueline R. M. A., et al.
Published: (2025)
by: Maasch, Jacqueline R. M. A., et al.
Published: (2025)
Granger Causality Detection with Kolmogorov-Arnold Networks
by: Lin, Hongyu, et al.
Published: (2024)
by: Lin, Hongyu, et al.
Published: (2024)
Causal Learner: A Toolbox for Causal Structure and Markov Blanket Learning
by: Ling, Zhaolong, et al.
Published: (2021)
by: Ling, Zhaolong, et al.
Published: (2021)
Local Causal Discovery for Statistically Efficient Causal Inference
by: Schubert, Mátyás, et al.
Published: (2025)
by: Schubert, Mátyás, et al.
Published: (2025)
FRIT: Using Causal Importance to Improve Chain-of-Thought Faithfulness
by: Swaroop, Anand, et al.
Published: (2025)
by: Swaroop, Anand, et al.
Published: (2025)
Enhancing the Performance of Neural Networks Through Causal Discovery and Integration of Domain Knowledge
by: Zhang, Xiaoge, et al.
Published: (2023)
by: Zhang, Xiaoge, et al.
Published: (2023)
Dynamic Expert-Guided Model Averaging for Causal Discovery
by: Tench, Adrick, et al.
Published: (2026)
by: Tench, Adrick, et al.
Published: (2026)
A Model of Causal Explanation on Neural Networks for Tabular Data
by: Isozaki, Takashi, et al.
Published: (2025)
by: Isozaki, Takashi, et al.
Published: (2025)
Algorithmic Primitives and Compositional Geometry of Reasoning in Language Models
by: Lippl, Samuel, et al.
Published: (2025)
by: Lippl, Samuel, et al.
Published: (2025)
DyC-STG: Dynamic Causal Spatio-Temporal Graph Network for Real-time Data Credibility Analysis in IoT
by: Cheng, Guanjie, et al.
Published: (2025)
by: Cheng, Guanjie, et al.
Published: (2025)
CausalCompass: Evaluating the Robustness of Time-Series Causal Discovery in Misspecified Scenarios
by: Yi, Huiyang, et al.
Published: (2026)
by: Yi, Huiyang, et al.
Published: (2026)
CausalGDP: Causality-Guided Diffusion Policies for Reinforcement Learning
by: Xiao, Xiaofeng, et al.
Published: (2026)
by: Xiao, Xiaofeng, et al.
Published: (2026)
Causal Composition Diffusion Model for Closed-loop Traffic Generation
by: Lin, Haohong, et al.
Published: (2024)
by: Lin, Haohong, et al.
Published: (2024)
A Human-Centered Privacy Approach (HCP) to AI
by: Sun, Luyi, et al.
Published: (2026)
by: Sun, Luyi, et al.
Published: (2026)
Similar Items
-
A Geometrically-Grounded Drive for MDL-Based Optimization in Deep Learning
by: Lei, Ming, et al.
Published: (2026) -
A Comparative Theoretical Analysis of Entropy Control Methods in Reinforcement Learning
by: Lei, Ming, et al.
Published: (2026) -
Geometric Meta-Learning via Coupled Ricci Flow: Unifying Knowledge Representation and Quantum Entanglement
by: Lei, Ming, et al.
Published: (2025) -
A Full DAG Score-Based Algorithm for Learning Causal Bayesian Networks with Latent Confounders
by: Gonzales, Christophe, et al.
Published: (2024) -
Understanding Hardness of Vision-Language Compositionality from A Token-level Causal Lens
by: Chen, Ziliang, et al.
Published: (2025)