Presented my poster on discovering plasticity rules to train recurrent networks in Rome at the 7th International Conference on the Mathematics of Neuroscience and AI (known also as NeuroMONSTER).
For a reason I cannot recall right now, I registered my poster under both Neural Theory and Neural Data, and since Neural Theory is always overcrowded (according to the organizers) my poster fell under the Neural Data category. Which ended up being rather fortunate for multiple reasons: - First, a couple of attendees who listened to my presentation, wondered at the end, “Well were are the neural data in this poster?” (hint: nowhere, yet :) ), which led up to discussions on how could one consider integrating neural data in the project. - Second, since the most fitting categories ended up being Neural Theory or Machine Learning, attendes interested in those fields didn’t have a lot of other posters to visit during that session, and my poster ended up being crowded. - Third, the Neural Theory poster session ended up being rather short, due to the planned conference dinner that followed.
In my defence, I had assumed that the Machine Learning session would focus on more hardcore machine-learning work. In practice, many of the presentations were closer to NeuroAI, so that session may actually have been the best fit for my poster.
I really enjoyed the conference, and it is a pity that I haven’t attended that before (even though it was initially taking place in Greece for the first iterations). I really enjoyed the talk of György Buzsáki, both for its content and its delivery.