Noise contrastive meta-learning for conditional density estimation using kernel mean embeddings
Current meta-learning approaches focus on learning functional representations of relationships between variables, i.e. estimating conditional expectations in regression. In many applications, however, the conditional distributions cannot be meaningfully summarized solely by expectation (due to e.g....
| Main Authors: | , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Journal of Machine Learning Research
2021
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