Lisa defended her PhD

Last week, Dr. Lisa Chabrier successfully defended her PhD work on calculating SHAP values and using them to do differential network analysis. Whilst SHAP values are a popular framework for local explanations of machine learning predictions, they come with a serious computational cost. Lisa developed an approximation algorithm to avoid calculating lots of SHAP values … [Read more…]

Our work published in Nature Neuroscience

Update on June 13th, 2025 I was interviewed for a short article on my institute’s website. You can read it here. Note that the article is in French, the English translation will follow soon. Original post Great news! Sara’s work on characterizing the neurons involved in odor interpretation has been published in Nature Neuroscience (see … [Read more…]

Bye bye Twitter!

Until this autumn I used to spend time on Twitter. I found many an interesting article casually browsing tweets and occasionally I would find a reason to write a tweet myself. Well, that’s history now. I may join a Mastodon server at some point, but for the moment I am going to enjoy the silence. … [Read more…]

What do we learn from evolutionary simulations?

Digital experiments of how the process of evolution works—also known as in silico (experimental) evolution or simply evolutionary simulations—have been explored and studied since the early days of computing. Nowadays, while using the computer to simulate evolution is a well-accepted approach, not everyone is clear about what it teaches us. As I use such simulations … [Read more…]