# New Teaching Material: Analyzing IGOR binary files of patch clamp recordings

I’ve added a new tutorial in the teaching section on how to read and process IGOR binary files (`*.ibw`

) of patch clamp recordings.

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less than 1 minute read
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I’ve added a new tutorial in the teaching section on how to read and process IGOR binary files (`*.ibw`

) of patch clamp recordings.

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11 minute read
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I was wondering whether it would be possible to let GANs generate samples conditioned on a specific input type. I wanted the GAN to generate samples of a spe...

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12 minute read
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We explore an alternative approach to implementing WGANs. Contrasting from the standard implementation that requires both a generator and discriminator, the...

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22 minute read
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We apply the Wasserstein distance to Generative Adversarial Networks (GANs) to train them more effectively. We compare a default GAN with a Wasserstein GAN (...

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14 minute read
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Probabilistic distance metrics play a crucial role in a broad range of machine learning tasks, including clustering, classification, and information retrieva...

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14 minute read
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In machine learning, especially when dealing with probability distributions or deep generative models, different metrics are used to quantify the ‘distance’ ...

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8 minute read
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In the previous two posts, we’ve discussed the mathematical details of the Wasserstein distance, exploring its formal definition, its computation through lin...

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10 minute read
updated:
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Calculating the Wasserstein distance can be computational costly when using linear programming. The Sinkhorn algorithm provides a computationally efficient m...

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26 minute read
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The Wasserstein distance, also known as the Earth Mover’s Distance (EMD), provides a robust and insightful approach for comparing probability distributions a...

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