Papers › Continuously Indexed Domain Adaptation
Continuously Indexed Domain Adaptation
Hao Wang, Hao He, Dina Katabi
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.
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Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Continuously Indexed Domain Adaptation | Circle | CIDA | Accuracy (%) | 94% | #1 of 1 | Archive leaderboard | report |
| Continuously Indexed Domain Adaptation | Indexed Rotating MNIST | PCIDA | Accuracy (%) | 87.1% | #1 of 2 | Archive leaderboard | report |
| Continuously Indexed Domain Adaptation | Indexed Rotating MNIST | CIDA | Accuracy (%) | 85.7% | #2 of 2 | Archive leaderboard | report |
| Continuously Indexed Domain Adaptation | Sine | CIDA | Accuracy (%) | 95% | #1 of 1 | Archive leaderboard | report |
| Domain Adaptation | Rotating MNIST | PCIDA | Accuracy (%) | 87.1% | #1 of 2 | Archive leaderboard | report |
| Domain Adaptation | Rotating MNIST | CIDA | Accuracy (%) | 85.7% | #2 of 2 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
Introduced by this paper: CIDA
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