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Found 5 papers, 3 papers with code
Algorithmic insights on continual learning from fruit flies
We discovered a two layer neural circuit in the fruit fly olfactory system that addresses this challenge by uniquely combining sparse coding and associative learning.
Can a Fruit Fly Learn Word Embeddings?
In this work we study a mathematical formalization of this network motif and apply it to learning the correlational structure between words and their context in a corpus of unstructured text, a common natural language processing (NLP) task.
Improving Similarity Search with High-dimensional Locality-sensitive Hashing
We propose a new class of data-independent locality-sensitive hashing (LSH) algorithms based on the fruit fly olfactory circuit.
Using inspiration from synaptic plasticity rules to optimize traffic flow in distributed engineered networks
Controlling the flow and routing of data is a fundamental problem in many distributed networks, including transportation systems, integrated circuits, and the Internet.
Distributed Gradient Descent in Bacterial Food Search
Communication and coordination play a major role in the ability of bacterial cells to adapt to ever changing environments and conditions.
Quantitative Methods
