Cover Image

Towards Causal Representation Learning with Observable Sources as Auxiliaries

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kim, Kwonho, Nam, Heejeong, Hwang, Inwoo, Lee, Sanghack
Format:	Preprint
Published:	2025
Subjects:	Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

PEER pressure: Model-to-Model Regularization for Single Source Domain Generalization
by: Cho, Dong Kyu, et al.
Published: (2025)

Fine-Grained Causal Dynamics Learning with Quantization for Improving Robustness in Reinforcement Learning
by: Hwang, Inwoo, et al.
Published: (2024)

Efficient Monte Carlo Tree Search via On-the-Fly State-Conditioned Action Abstraction
by: Kwak, Yunhyeok, et al.
Published: (2024)

On Discovery of Local Independence over Continuous Variables via Neural Contextual Decomposition
by: Hwang, Inwoo, et al.
Published: (2024)

From Black-box to Causal-box: Towards Building More Interpretable Models
by: Hwang, Inwoo, et al.
Published: (2025)

Mitigating Length Bias in RLHF through a Causal Lens
by: Kim, Hyeonji, et al.
Published: (2025)

An Adversarial Learning Approach to Irregular Time-Series Forecasting
by: Nam, Heejeong, et al.
Published: (2024)

Causal-JEPA: Learning World Models through Object-Level Latent Masking
by: Nam, Heejeong, et al.
Published: (2026)

On Predicting Post-Click Conversion Rate via Counterfactual Inference
by: Ahn, Junhyung, et al.
Published: (2025)

Estimating Covariance for Global Minimum Variance Portfolio: A Decision-Focused Learning Approach
by: Kim, Juchan, et al.
Published: (2025)

Versatile Physics-based Character Control with Hybrid Latent Representation
by: Bae, Jinseok, et al.
Published: (2025)

Multi-View Causal Representation Learning with Partial Observability
by: Yao, Dingling, et al.
Published: (2023)

A Sparsity Principle for Partially Observable Causal Representation Learning
by: Xu, Danru, et al.
Published: (2024)

Auxiliary Reward Generation with Transition Distance Representation Learning
by: Li, Siyuan, et al.
Published: (2024)

Toward Temporal Causal Representation Learning with Tensor Decomposition
by: Chen, Jianhong, et al.
Published: (2025)

Human-Aligned Procedural Level Generation Reinforcement Learning via Text-Level-Sketch Shared Representation
by: Baek, In-Chang, et al.
Published: (2025)

Learning Semantic Information from Raw Audio Signal Using Both Contextual and Phonetic Representations
by: Kim, Jaeyeon, et al.
Published: (2024)

Locality-aware Concept Bottleneck Model
by: Jeon, Sujin, et al.
Published: (2025)

Causal Imitation Learning under Expert-Observable and Expert-Unobservable Confounding
by: Shao, Daqian, et al.
Published: (2025)

Feature-Centric Unsupervised Node Representation Learning Without Homophily Assumption
by: Kim, Sunwoo, et al.
Published: (2025)

Towards the Reusability and Compositionality of Causal Representations
by: Talon, Davide, et al.
Published: (2024)

Time, Causality, and Observability Failures in Distributed AI Inference Systems
by: Sharma, Ankur, et al.
Published: (2026)

Representation Learning of Auxiliary Concepts for Improved Student Modeling and Exercise Recommendation
by: Badran, Yahya, et al.
Published: (2025)

Provable Representation with Efficient Planning for Partial Observable Reinforcement Learning
by: Zhang, Hongming, et al.
Published: (2023)

Towards Robust Trajectory Representations: Isolating Environmental Confounders with Causal Learning
by: Luo, Kang, et al.
Published: (2024)

Temporal Representation Learning for Stock Similarities and Its Applications in Investment Management
by: Hwang, Yoontae, et al.
Published: (2024)

Multi-Objective Instruction-Aware Representation Learning in Procedural Content Generation RL
by: Kim, Sung-Hyun, et al.
Published: (2025)

PAC-Bayesian Generalization Bounds for Knowledge Graph Representation Learning
by: Lee, Jaejun, et al.
Published: (2024)

EmoSphere-SER: Enhancing Speech Emotion Recognition Through Spherical Representation with Auxiliary Classification
by: Cho, Deok-Hyeon, et al.
Published: (2025)

Towards Interpretable Deep Generative Models via Causal Representation Learning
by: Moran, Gemma E., et al.
Published: (2025)

Universal Time-Series Representation Learning: A Survey
by: Trirat, Patara, et al.
Published: (2024)

Localized Concept Erasure in Text-to-Image Diffusion Models via High-Level Representation Misdirection
by: Lee, Uichan, et al.
Published: (2026)

SAE-RNA: A Sparse Autoencoder Model for Interpreting RNA Language Model Representations
by: Kim, Taehan, et al.
Published: (2025)

Why and How Auxiliary Tasks Improve JEPA Representations
by: Yu, Jiacan, et al.
Published: (2025)

Causality-informed Anomaly Detection in Partially Observable Sensor Networks: Moving beyond Correlations
by: Xiao, Xiaofeng, et al.
Published: (2025)

Multi-View Node Pruning for Accurate Graph Representation
by: Kim, Hanjin, et al.
Published: (2025)

Pessimistic Auxiliary Policy for Offline Reinforcement Learning
by: Zhang, Fan, et al.
Published: (2026)

Richer Representations for Neural Algorithmic Reasoning via Auxiliary Reconstruction
by: Huang, Jiafu, et al.
Published: (2026)

Cross-lingual Back-Parsing: Utterance Synthesis from Meaning Representation for Zero-Resource Semantic Parsing
by: Kang, Deokhyung, et al.
Published: (2024)

Uncertainty Representations in State-Space Layers for Deep Reinforcement Learning under Partial Observability
by: Luis, Carlos E., et al.
Published: (2024)