Highlights from Neuromatch 4.0 Conference

• nma-cn-project

  1 3 1.8 Jupyter Notebook

  Project for Neuromatch Academy: Computational Neuroscience

As someone who has worked on analyzing V1 before[2], I was especially interested in this work. The authors inquire whether SST or VIP interneurons respond more strongly to novel visual stimuli. They use statistical ML techniques with 8-fold cross validation to predict the stimulus response.

• fliscopt

  4 39 2.3 Python

  Algorithms for flight scheduling optimization.

This poster is interesting for anyone who finds concepts of attention mechanisms, Genetic algorithms interesting. In this poster the authors present an interesting idea as to how, switching mechanisms are responsible for improvements in biological organisms as well as in simulated beings. They take this idea to an extreme by implementing “switching” within an algorithm (Inter algorithmic switching) to between two diff algorithms (Intra algorithmic switching).

• InfluxDB

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  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

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