thoughtidearepresentation-learning
motivation
- each piece of information has its own representation
- different tasks might require different amount of information
- it is not practical to represent all information in one latent space
- information could be different in various characteristics: modality, domain, complexity
- represent everything in one giant space is not efficient
Hence, the representations need to be combined losslessly
- from the combination, we should be able to get back each component
- one simple way is concatenation
- or using multiple modular modules
How to design an architecture that would be able to work with dynamic-sized representations ?question Do we still need, at some point, a unified latent space ?