mlsanityData to 7 Oct 2026

Continuously Indexed Domain Adaptation

arXiv 2007.01807 ↗First posted 3 Jul 2020cs.LG cs.CV cs.NEcited by 74

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Abstract (arXiv)

Existing domain adaptation focuses on transferring knowledge between domains with categorical indices (e.g., between datasets A and B). However, many tasks involve continuously indexed domains. For example, in medical applications, one often needs to transfer disease analysis and prediction across patients of different ages, where age acts as a continuous domain index. Such tasks are challenging for prior domain adaptation methods since they ignore the underlying relation among domains. In this paper, we propose the first method for continuously indexed domain adaptation. Our approach combines traditional adversarial adaptation with a novel discriminator that models the encoding-conditioned domain index distribution. Our theoretical analysis demonstrates the value of leveraging the domain index to generate invariant features across a continuous range of domains. Our empirical results show that our approach outperforms the state-of-the-art domain adaption methods on both synthetic and real-world medical datasets.

Key facts. Cited by 74 papers in the map (data through 7 Oct 2026). First posted on arXiv 3 Jul 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 14; 2022: 19; 2023: 20; 2024: 12; 2025: 4; 2026: 5.

74 papers.

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  1. 2021Generalizing to Unseen Domains: A Survey on Domain Generalizationcited by 762
  2. 2021Delving into Deep Imbalanced Regressioncited by 157
  3. 2021Domain Adaptation for Time Series Forecasting via Attention Sharingcited by 68
  4. 2023AdaNPC: Exploring Non-Parametric Classifier for Test-Time Adaptationcited by 48
  5. 2023Free Lunch for Domain Adversarial Training: Environment Label Smoothingcited by 33
  6. 2024Energy-Based Concept Bottleneck Models: Unifying Prediction, Concept Intervention, and Probabilistic Interpretationscited by 33
  7. 2022Understanding Gradual Domain Adaptation: Improved Analysis, Optimal Path and Beyondcited by 32
  8. 2022Temporal Domain Generalization with Drift-Aware Dynamic Neural Networkscited by 32
  9. 2023A Unified Approach to Domain Incremental Learning with Memory: Theory and Algorithmcited by 32
  10. 2022Out-of-Distribution Representation Learning for Time Series Classificationcited by 30
  11. 2021When Age-Invariant Face Recognition Meets Face Age Synthesis: A Multi-Task Learning Frameworkcited by 29
  12. 2021Self-Adversarial Disentangling for Specific Domain Adaptationcited by 29
38 more
  1. 2022Curriculum Reinforcement Learning using Optimal Transport via Gradual Domain Adaptationcited by 28
  2. 2021Learngene: From Open-World to Your Learning Taskcited by 27
  3. 2021Training for the Future: A Simple Gradient Interpolation Loss to Generalize Along Timecited by 27
  4. 2022Exploring Transformer Backbones for Heterogeneous Treatment Effect Estimationcited by 25
  5. 2024Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Datacited by 25
  6. 2023DIVERSIFY: A General Framework for Time Series Out-of-distribution Detection and Generalizationcited by 24
  7. 2023ManyDG: Many-domain Generalization for Healthcare Applicationscited by 23
  8. 2022Domain Generalization via Frequency-domain-based Feature Disentanglement and Interactioncited by 21
  9. 2024On Calibration of LLM-based Guard Models for Reliable Content Moderationcited by 21
  10. 2022Graph-Relational Domain Adaptationcited by 19
  11. 2023Domain-Indexing Variational Bayes: Interpretable Domain Index for Domain Adaptationcited by 19
  12. 2022Generalizing to Evolving Domains with Latent Structure-Aware Sequential Autoencodercited by 18
  13. 2023Gradual Domain Adaptation: Theory and Algorithmscited by 18
  14. 2023CF-GODE: Continuous-Time Causal Inference for Multi-Agent Dynamical Systemscited by 16
  15. 2024Continuous Temporal Domain Generalizationcited by 14
  16. 2025Learning Robust Spectral Dynamics for Temporal Domain Generalizationcited by 13
  17. 2024Generalizing across Temporal Domains with Koopman Operatorscited by 12
  18. 2022Gradual Domain Adaptation via Normalizing Flowscited by 11
  19. 2023Foresee What You Will Learn: Data Augmentation for Domain Generalization in Non-stationary Environmentcited by 11
  20. 2023Meta OOD Learning for Continuously Adaptive OOD Detectioncited by 10
  21. 2023Adversarially Balanced Representation for Continuous Treatment Effect Estimationcited by 10
  22. 2022FedDAR: Federated Domain-Aware Representation Learningcited by 8
  23. 2021Automatic Online Multi-Source Domain Adaptationcited by 7
  24. 2022When Age-Invariant Face Recognition Meets Face Age Synthesis: A Multi-Task Learning Framework and A New Benchmarkcited by 7
  25. 2023EvoluNet: Advancing Dynamic Non-IID Transfer Learning on Graphscited by 7
  26. 2022Domain Adaptation with Factorizable Joint Shiftcited by 6
  27. 2022Delving into the Continuous Domain Adaptationcited by 6
  28. 2023Taxonomy-Structured Domain Adaptationcited by 6
  29. 2023CODA: Temporal Domain Generalization via Concept Drift Simulatorcited by 6
  30. 2023Continuous Invariance Learningcited by 6
  31. 2024Causal Machine Learning for Cost-Effective Allocation of Development Aidcited by 6
  32. 2022A Unified Meta-Learning Framework for Dynamic Transfer Learningcited by 5
  33. 2023Cross-Frequency Time Series Meta-Forecastingcited by 5
  34. 2023Evolving Domain Adaptation of Pretrained Language Models for Text Classificationcited by 5
  35. 2025Concept-Based Unsupervised Domain Adaptationcited by 4
  36. 2021Adaptive Feature Alignment for Adversarial Trainingcited by 3
  37. 2021A Bayesian Approach to (Online) Transfer Learning: Theory and Algorithmscited by 3
  38. 2022Cost-effective Framework for Gradual Domain Adaptation with Multifidelitycited by 3

50 most cited of 74 All 74 (JSON)