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| ICNN: INPUT-CONDITIONED FEATURE REPRESENTATION LEARNING FOR TRANSFORMATION-INVARIANT NEURAL NETWORK | Sep 25, 2019 | DecoderRepresentation Learning | —Unverified | 0 |
| Improving the Sample-Complexity of Deep Classification Networks with Invariant Integration | Feb 8, 2022 | Rotated MNIST | —Unverified | 0 |
| DIVA: Domain Invariant Variational Autoencoder | Mar 27, 2019 | Domain GeneralizationRotated MNIST | —Unverified | 0 |
| Generalizing to Unseen Domains with Wasserstein Distributional Robustness under Limited Source Knowledge | Jul 11, 2022 | Domain GeneralizationRotated MNIST | —Unverified | 0 |
| Co-Attentive Equivariant Neural Networks: Focusing Equivariance On Transformations Co-Occurring In Data | Nov 18, 2019 | Object RecognitionRotated MNIST | —Unverified | 0 |
| GDO: Gradual Domain Osmosis | Jan 31, 2025 | Domain AdaptationRotated MNIST | —Unverified | 0 |
| Deformable Classifiers | Dec 18, 2017 | ObjectObject Recognition | —Unverified | 0 |
| Fast Inference in Capsule Networks Using Accumulated Routing Coefficients | Apr 15, 2019 | ObjectRotated MNIST | —Unverified | 0 |
| What's Inside Your Diffusion Model? A Score-Based Riemannian Metric to Explore the Data Manifold | May 16, 2025 | NavigateRotated MNIST | —Unverified | 0 |
