Invariant Models for Causal Transfer Learning

No abstract is available for this paper.

• Publication year

  2015

• Venue

  Journal of machine learning research

• Publication date

  2015-07-19

• Fields of study

  Computer Science

• Identifiers

  No identifiers available.

• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Invariant Causal Prediction for Nonlinear Models

  2017cited by this paper
• Elements of Causal Inference: Foundations and Learning Algorithms

  2017cited by this paper
• Distinguishing Cause from Effect Based on Exogeneity

  2015cited by this paper
• Causal inference by using invariant prediction: identification and confidence intervals

  2015cited by this paper
• Multi-Source Domain Adaptation: A Causal View

  2015cited by this paper
• Large-scale genetic perturbations reveal regulatory networks and an abundance of gene-specific repressors.

  2014cited by this paper
• Statistics for High-Dimensional Data: Methods, Theory and Applications, Peter Buhlman and Sara van de Geer著, Springer, 2011年6月, 558pp., 価格 114,99〓, ISBN 978-3642201912

  2014cited by this paper
• Maximum likelihood estimation for linear Gaussian covariance models

  2014cited by this paper
• Deep learning in neural networks: An overview

  2014cited by this paper
• Domain Generalization via Invariant Feature Representation

  2013influential reference
• Domain Adaptation under Target and Conditional Shift

  2013cited by this paper
• Marginalized Denoising Autoencoders for Domain Adaptation

  2012influential reference
• ImageNet classification with deep convolutional neural networks

  2012cited by this paper
• Exploiting Unrelated Tasks in Multi-Task Learning

  2012cited by this paper
• On causal and anticausal learning

  2012influential reference
• Kernel-based Conditional Independence Test and Application in Causal Discovery

  2011cited by this paper
• Impossibility Theorems for Domain Adaptation

  2010cited by this paper
• A Survey on Transfer Learning

  2010cited by this paper
• The Logic of Causal Inference

  2010cited by this paper
• Frustratingly Easy Semi-Supervised Domain Adaptation

  2010cited by this paper
• Dataset Shift in Machine Learning

  2009cited by this paper
• Covariate Shift by Kernel Mean Matching

  2009cited by this paper
• An Empirical Analysis of Domain Adaptation Algorithms for Genomic Sequence Analysis

  2008cited by this paper
• Causal Inference Using the Algorithmic Markov Condition

  2008cited by this paper
• Knowledge transfer via multiple model local structure mapping

  2008cited by this paper
• A Kernel Statistical Test of Independence

  2007influential reference
• Self-taught learning: transfer learning from unlabeled data

  2007cited by this paper
• Kernel Measures of Conditional Dependence

  2007cited by this paper
• Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation

  2007cited by this paper
• A Spectral Regularization Framework for Multi-Task Structure Learning

  2007cited by this paper
• Multi-task Gaussian Process Prediction

  2007cited by this paper
• Learning to learn with the informative vector machine

  2004cited by this paper
• Regularized multi--task learning

  2004cited by this paper
• Task Clustering and Gating for Bayesian Multitask Learning

  2003cited by this paper
• Toward a perception-based theory of probabilistic reasoning with imprecise probabilities

  2002cited by this paper
• A Model of Inductive Bias Learning

  2000cited by this paper
• Multitask Learning

  1997cited by this paper
• Regression Shrinkage and Selection via the Lasso

  1996influential reference
• Statistical Analysis With Missing Data

  1988cited by this paper
• On the logic of causal inference.

  1986influential reference
• Contributions to Probability and Statistics: Essays in Honor of Harold Hotelling.

  1962cited by this paper
• Robust tests for equality of variances

  1961cited by this paper
• Causality : Models , Reasoning , and Inference

  year unknowninfluential reference

• Causality-Informed Neural Networks for Regularized Learning in Regression Problems

  2026cites this paper
• An Expectation-Maximization Algorithm for Domain Adaptation in Gaussian Causal Models

  2026cites this paper
• Towards OOD Generalization in Dynamic Graphs via Causal Invariant Learning

  2026cites this paper
• Anti-causal domain generalization: Leveraging unlabeled data

  2026cites this paper
• FGRW: Fine-Grained Reversible Watermarking Based on Distribution-Adaptive Contrastive Augmentation Across Diverse Domains

  2026cites this paper
• On the Non-Identifiability of Steering Vectors in Large Language Models

  2026cites this paper
• Environment-Adaptive Covariate Selection: Learning When to Use Spurious Correlations for Out-of-Distribution Prediction

  2026cites this paper
• Molecular graph-based invariant representation learning with environmental inference and subgraph generation for out-of-distribution generalization

  2026cites this paper
• On the integration of Domain Adaptation and Causal Discovery in Digital Twins: A Case Study for Plastic Injection Molding

  2026cites this paper
• CAMEL-Dx: A Causal Meta-Learning Framework for Rare Disease Diagnosis with Limited Samples

  2026cites this paper
• Personalizing black-box models for nonparametric regression with minimax optimality

  2026cites this paper
• CFSM: A Novel Causal Feature Selection Module for Two-Dimensional Out-of-Distribution Generalization

  2026cites this paper
• Causally-Aware Information Bottleneck for Domain Adaptation

  2026cites this paper
• Achievable distributional robustness when the robust risk is only partially identified

  2025cites this paper
• Partial Transportability for Domain Generalization

  2025cites this paper
• Causally-informed Deep Learning towards Explainable and Generalizable Outcomes Prediction in Critical Care

  2025cites this paper
• On the Value of Cross-Modal Misalignment in Multimodal Representation Learning

  2025cites this paper
• Causal Mechanism Estimation in Multi-Sensor Systems Across Multiple Domains

  2025cites this paper
• The Third Pillar of Causal Analysis? A Measurement Perspective on Causal Representations

  2025cites this paper
• Learning Pareto manifolds in high dimensions: How can regularization help?

  2025cites this paper
• Causal Meta-Learning for Few-Shot Threat Detection in NIDS

  2025cites this paper
• Enhancing Out-of-distribution Generalization for Graph Learning with Causal Information Bottleneck

  2025cites this paper
• From Small to Large: In-Context Learning as a New Paradigm for Domain Generalization

  2025cites this paper
• A New Perspective on AI Safety Through Control Theory Methodologies

  2025cites this paper
• Negate or Embrace: On How Misalignment Shapes Multimodal Representation Learning

  2025cites this paper
• InvMOE: MOEs Based Invariant Representation Learning for Fault Detection in Converter Stations

  2025cites this paper
• Causal inference-based dynamic optimization for disassembly line balancing with uncertain component states

  2025cites this paper
• PrAda-GAN: A Private Adaptive Generative Adversarial Network with Bayes Network Structure

  2025cites this paper
• SCMD: A Kernel-Based Distance for Structural Causal Models to Quantify Transferability Across Environments

  2025cites this paper
• Advantages and limitations in the use of transfer learning for individual treatment effects in causal machine learning

  2025cites this paper
• iROAS-Based Dynamic Bidding Strategy Using Multi-Armed Bandits in Retail Media Networks

  2025cites this paper
• Bridging Distribution Shift and AI Safety: Conceptual and Methodological Synergies

  2025cites this paper
• InfoBound: A Provable Information-Bounds Inspired Framework for Both OoD Generalization and OoD Detection

  2025cites this paper
• Feature Matching Intervention: Leveraging Observational Data for Causal Representation Learning

  2025cites this paper
• The Relativity of Causal Knowledge

  2025cites this paper
• Bayesian Invariance Modeling of Multi-Environment Data

  2025cites this paper
• Causality-Inspired Robustness for Nonlinear Models via Representation Learning

  2025cites this paper
• When Shift Happens - Confounding Is to Blame

  2025cites this paper
• Causality in the human niche: lessons for machine learning

  2025cites this paper
• Physics-informed transfer learning for SHM via feature selection

  2025influential citation
• Robust Optimization in Causal Models and G-Causal Normalizing Flows

  2025cites this paper
• T5-based anomaly-behavior video captioning using semantic relation mining

  2025cites this paper
• Maximum Risk Minimization with Random Forests

  2025cites this paper
• Evolving Graph Learning for Out-of-Distribution Generalization in Non-Stationary Environments

  2025cites this paper
• Causality-Driven Convolutional Manifold Attention Network for Electroencephalogram Signal Decoding

  2025cites this paper
• Transferring Causal Effects using Proxies

  2025cites this paper
• Adapting, Fast and Slow: Transportable Circuits for Few-Shot Learning

  2025cites this paper
• Stable Subsampling under Model Misspecification and Covariate Shift

  2025cites this paper
• IIB-DDI: Invariant Information Bottleneck Theory for Out-of-Distribution Drug-Drug Interaction Prediction

  2025cites this paper
• Uncertainty Sets for Distributionally Robust Bandits Using Structural Equation Models

  2025cites this paper
• Causal-aware Graph Neural Architecture Search under Distribution Shifts

  2025cites this paper
• Vision Transformer Neural Architecture Search for Out-of-Distribution Generalization: Benchmark and Insights

  2025cites this paper
• MSVnet: A multi-scale and multi-view discriminator for fish detection in unseen domain

  2025cites this paper
• What makes a forest growth model climate-sensitive? An examination of statistical and silvicultural model needs under climate change

  2025cites this paper
• EM-Based Transfer Learning for Gaussian Causal Models Under Covariate and Target Shift

  2025cites this paper
• Federated Domain Generalization Based on Invariant Learning for Multi-Unmanned Systems

  2025cites this paper
• Fast and robust invariant generalized linear models.

  2025cites this paper
• Aprendizaje anticausal en problemas inversos y su aplicación a tomografía optoacústica

  2025cites this paper
• I3-MRec: Invariant Learning with Information Bottleneck for Incomplete Modality Recommendation

  2025cites this paper
• Efficient Identification of Direct Causal Parents via Invariance and Minimum Error Testing

  2024cites this paper
• Few-shot Multi-Task Learning of Linear Invariant Features with Meta Subspace Pursuit

  2024cites this paper
• CPI-Parser: Integrating Causal Properties Into Multiple Human Parsing

  2024cites this paper
• CaTs and DAGs: Integrating Directed Acyclic Graphs with Transformers and Fully-Connected Neural Networks for Causally Constrained Predictions

  2024cites this paper
• Mixstyle-Entropy: Domain Generalization with Causal Intervention and Perturbation

  2024cites this paper
• Causal Deep Learning: Encouraging Impact on Real-world Problems Through Causality

  2024cites this paper
• Causal Discovery from Time-Series Data with Short-Term Invariance-Based Convolutional Neural Networks

  2024cites this paper
• Unifying Causal Representation Learning with the Invariance Principle

  2024cites this paper
• Weighted Risk Invariance: Domain Generalization under Invariant Feature Shift

  2024cites this paper
• Causality for Large Language Models

  2024cites this paper
• CaTs and DAGs: Integrating Directed Acyclic Graphs with Transformers for Causally Constrained Predictions

  2024cites this paper
• Self-Distilled Disentangled Learning for Counterfactual Prediction

  2024cites this paper
• Open-Set Single-Domain Generalization for Robust Face Anti-Spoofing

  2024cites this paper
• Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant Learning

  2024influential citation
• Cin-Seg: Causal Invariance for Tag-Supervised Segmentation on Medical Images

  2024cites this paper
• Learning When the Concept Shifts: Confounding, Invariance, and Dimension Reduction

  2024cites this paper
• Causally Abstracted Multi-armed Bandits

  2024cites this paper
• Mining Invariance from Nonlinear Multi-Environment Data: Binary Classification

  2024cites this paper
• Causality Pursuit from Heterogeneous Environments via Neural Adversarial Invariance Learning

  2024cites this paper
• Causal Modeling in Multi-Context Systems: Distinguishing Multiple Context-Specific Causal Graphs which Account for Observational Support

  2024cites this paper
• FAIRM: Learning invariant representations for algorithmic fairness and domain generalization with minimax optimality

  2024cites this paper
• A Causality-Aware Perspective on Domain Generalization via Domain Intervention

  2024cites this paper
• Domain Generalisation via Imprecise Learning

  2024cites this paper
• Random color transformation for single domain generalized retinal image segmentation

  2024cites this paper
• Pairwise Alignment Improves Graph Domain Adaptation

  2024cites this paper
• OTClean: Data Cleaning for Conditional Independence Violations using Optimal Transport

  2024cites this paper
• Invariant Feature Learning Based on Causal Inference from Heterogeneous Environments

  2024cites this paper
• On Provable Length and Compositional Generalization

  2024cites this paper
• HYPO: Hyperspherical Out-of-Distribution Generalization

  2024cites this paper
• Towards Robust Out-of-Distribution Generalization Bounds via Sharpness

  2024cites this paper
• Graph Out-of-Distribution Generalization via Causal Intervention

  2024cites this paper
• Few-Shot Causal Representation Learning for Out-of-Distribution Generalization on Heterogeneous Graphs

  2024cites this paper
• A Causal Inspired Early-Branching Structure for Domain Generalization

  2024cites this paper
• HCVP: Leveraging Hierarchical Contrastive Visual Prompt for Domain Generalization

  2024cites this paper
• The Propensity-Weighted Causal Learner (PWCL) for Efficient Machine Learning

  2024cites this paper
• Advanced Methodologies and Technologies for Innovative Information Systems

  2024cites this paper
• Causal Invariance Learning via Efficient Optimization of a Nonconvex Objective

  2024cites this paper
• Mixstyle-Entropy: Whole Process Domain Generalization with Causal Intervention and Perturbation

  2024cites this paper
• Multi-environment prediction of suicidal beliefs

  2024cites this paper
• A Simple Data Augmentation for Graph Classification: A Perspective of Equivariance and Invariance

  2024cites this paper
• Invariant Feature Selection for Battery State of Health Estimation in Heterogeneous Hybrid Electric Bus Fleets

  2024influential citation