Gaussian Recipes for Rotational Spectroscopy

Recently I’ve had to do a few calculations using Gaussian where I had to keep going back and waste time to find out how to do something again. I basically got fed up with this, and I’m organizing this post to more or less create a cheatsheet that tells you how, and which keywords to use for calculations using Gaussian ‘09/’16 to do with spectroscopy, and where to look for the outputs.

Replacing proprietary software with open-source

Up until today, one of the primary methods of analyzing older data (actually stored on floppy disks!) in our lab was to use a specific Windows XP computer that runs a specific version of National Instruments LabView (7.0), which has a specific version of code that was written in the 2000’s specifically for this purpose.

Why Variational Autoencoders Need to Reparameterize

Today, I thought I had a stroke of brilliance by starting to develop a Linear layer in PyTorch that would have its parameters drawn from a Gaussian. My idea was to implement a Bayesian neural network, where the parameters of the network are treated as probability distributions, rather than just simple point estimates. In terms of Bayes rule:

Compressing Files in Linux

Here’s a quick post about a topic I find myself revisiting every few months: how to compress large batches of files efficiently. As I perform lots of calculations on a computing cluster, I like to routinely back things up at around publication time: that way I can have access to the data at the point where my paper was submitted, for example, and come back to it at a later date.


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