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Found 2 papers, 1 papers with code
Approaching an unknown communication system by latent space exploration and causal inference
This paper suggests that an interpretation of the outputs of deep neural networks with causal inference methodology can be a viable strategy for approaching data about which little is known and presents another case of how deep learning can limit the hypothesis space.
Cetacean Translation Initiative: a roadmap to deciphering the communication of sperm whales
We posit that machine learning will be the cornerstone of future collection, processing, and analysis of multimodal streams of data in animal communication studies, including bioacoustic, behavioral, biological, and environmental data.
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