Thanks to all great co-authors and collaborators who made these exciting research projects possible!

It is exciting to see how network science and interpretable AI can better inform and elucidate on psychological mechanisms concerning phenomena as complex as loneliness, anxiety and schizotipy.

Covarying gray and white matter networks characterize schizophrenia and bipolar disorders on a continuum: A data fusion machine learning approach and a brain network analysis, Journal of Affective Disorders, doi.org/10.1016/j.ja...

Cognitive Networks and Text Analysis Identify Anxiety as a Key Dimension of Distress in Genuine Suicide Notes, Big Data and Cognitive Science, doi.org/10.3390/bdcc...

I agree with you. In cognitive science, dual coding theory posits that reasoning relies on two processes: instinctive, rapid yet error-prone reasoning and analytical, slow-yet-balanced thinking. LLMs are not built to filter knowledge and use different processes, yet.

Thank you so much for inviting me! The organisation and the other talks at the conference have been excellent!

Looks super intriguing! We will organise something remote in the fall too! If you want to visit our lab in Trento let me know! With a postdoc and a PhD student we are working on a Python package for turning narratives into hypergraphs.

Totally, very excited about it!

I look forward to this! Funny thing: we are also working on this topic with @giuliorossetti.bsky.social. We tested associative knowledge in different layers and different LLMs and... Let's chat about this if you want ;)

Given the times, seaborn sounds as sketchy as numpy, alas!