Image de couverture de livre

Causal Learning with the Invariance Principle

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Montagna, Francesco, Locatello, Francesco
Format:	Preprint
Publié:	2026
Sujets:	Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

On the Identifiability of Causal Graphs with the Invariance Principle
par: Montagna, Francesco
Publié: (2025)

Unifying Causal Representation Learning with the Invariance Principle
par: Yao, Dingling, et autres
Publié: (2024)

The Rate-Distortion-Polysemanticity Tradeoff in SAEs
par: Mencattini, Tommaso, et autres
Publié: (2026)

Demystifying amortized causal discovery with transformers
par: Montagna, Francesco, et autres
Publié: (2024)

Marrying Causal Representation Learning with Dynamical Systems for Science
par: Yao, Dingling, et autres
Publié: (2024)

Exploratory Causal Inference in SAEnce
par: Mencattini, Tommaso, et autres
Publié: (2025)

Score matching through the roof: linear, nonlinear, and latent variables causal discovery
par: Montagna, Francesco, et autres
Publié: (2024)

A Sparsity Principle for Partially Observable Causal Representation Learning
par: Xu, Danru, et autres
Publié: (2024)

Controlling Transient Amplification Improves Long-horizon Rollouts
par: Pervez, Adeel, et autres
Publié: (2026)

The Third Pillar of Causal Analysis? A Measurement Perspective on Causal Representations
par: Yao, Dingling, et autres
Publié: (2025)

Addressing Instrument-Outcome Confounding in Mendelian Randomization through Representation Learning
par: Huang, Shimeng, et autres
Publié: (2026)

Learning Discrete Diffusion of Graphs via Free-Energy Gradient Flows
par: Rancati, Dario, et autres
Publié: (2026)

Smoke and Mirrors in Causal Downstream Tasks
par: Cadei, Riccardo, et autres
Publié: (2024)

Assumption violations in causal discovery and the robustness of score matching
par: Montagna, Francesco, et autres
Publié: (2023)

Identifying General Mechanism Shifts in Linear Causal Representations
par: Chen, Tianyu, et autres
Publié: (2024)

Toward Identifiable Sparse Autoencoders
par: Nelson, Walter, et autres
Publié: (2026)

Mechanistic PDE Networks for Discovery of Governing Equations
par: Pervez, Adeel, et autres
Publié: (2025)

Mechanistic Neural Networks for Scientific Machine Learning
par: Pervez, Adeel, et autres
Publié: (2024)

Towards a holistic understanding of Selection Bias for Causal Effect Identification
par: Qiu, Yiwen, et autres
Publié: (2026)

Prediction-Powered Causal Inferences
par: Cadei, Riccardo, et autres
Publié: (2025)

Self-Compatibility: Evaluating Causal Discovery without Ground Truth
par: Faller, Philipp M., et autres
Publié: (2023)

Multi-View Causal Representation Learning with Partial Observability
par: Yao, Dingling, et autres
Publié: (2023)

Out-of-Distribution Detection with Relative Angles
par: Demirel, Berker, et autres
Publié: (2024)

Statistical and structural identifiability in representation learning
par: Nelson, Walter, et autres
Publié: (2026)

High-dimensional Analysis of Synthetic Data Selection
par: Rezaei, Parham, et autres
Publié: (2025)

Navigating the Latent Space Dynamics of Neural Models
par: Fumero, Marco, et autres
Publié: (2025)

Scalable Mechanistic Neural Networks for Differential Equations and Machine Learning
par: Chen, Jiale, et autres
Publié: (2024)

Binding Dynamics in Rotating Features
par: Löwe, Sindy, et autres
Publié: (2024)

The Perception-Physics Paradox: Probing Scientific Alignment with TC-Bench
par: Yao, Dingling, et autres
Publié: (2026)

Latent Space Translation via Inverse Relative Projection
par: Maiorca, Valentino, et autres
Publié: (2024)

Scalable unsupervised alignment of general metric and non-metric structures
par: Vedula, Sanketh, et autres
Publié: (2024)

Latent Functional Maps: a spectral framework for representation alignment
par: Fumero, Marco, et autres
Publié: (2024)

MorphGen: Controllable and Morphologically Plausible Generative Cell-Imaging
par: Demirel, Berker, et autres
Publié: (2025)

Connecting Neural Models Latent Geometries with Relative Geodesic Representations
par: Yu, Hanlin, et autres
Publié: (2025)

Latent Space Translation via Semantic Alignment
par: Maiorca, Valentino, et autres
Publié: (2023)

Efficient Hyperparameter Tuning via Trajectory Invariance Principle
par: Li, Bingrui, et autres
Publié: (2025)

Identifiable Object-Centric Representation Learning via Probabilistic Slot Attention
par: Kori, Avinash, et autres
Publié: (2024)

Learning Local Causal World Models with State Space Models and Attention
par: Petri, Francesco, et autres
Publié: (2025)

Grounded Object Centric Learning
par: Kori, Avinash, et autres
Publié: (2023)

ResiDual Transformer Alignment with Spectral Decomposition
par: Basile, Lorenzo, et autres
Publié: (2024)