Workshop

Analytical Connectionism Workshop

Connectionism is a theoretical approach in psychology that uses neural-network models to simulate a wide range of cognitive phenomena such as perception, memory, decision-making, language, and cognitive control. However, the "black box" nature of most connectionist models limits our understanding of the mathematical principles underlying their behaviours. Recent progress in theoretical neuroscience and machine learning has provided novel analytical tools that have made it possible to explore these "black boxes" and gain a deeper understanding of connectionist models.

This 1.5-day workshop aims to bring together researchers in neuroscience, psychology, and machine learning to discuss the state of the art of research in connectionist theories of higher-level cognition and psychology, as well as the latest theoretical and analytical methods for analysing neural networks.

The workshop will cover a broad range of topics, including advances in analytical methods for neural-network analysis, novel experimental results that require theoretical explanation, and the most recent modelling efforts. The goal is to provide participants with a comprehensive overview of the latest developments in the field and to foster collaboration and discussion among researchers from different backgrounds.

Confirmed Speakers

• Francesco Cagnetta, EPFL
• Erin Grant, Gatsby Unit and Sainsbury Wellcome Centre
• Alessandro Ingrosso, ICTP
• Hadar Karmazyn Raz, Indiana University
• Jay McClelland, Stanford University
• Maneesh Sahani, Gatsby Unit
• Stefano Sarao Mannelli, Gatsby Unit

How to Apply

Application is now closed.

 

Information for Course Attendees

Analytical Connectionism Summer Course attendees will be automatically registered for the workshop and are expected to attend. There is no need to apply separately to the workshop unless you want to be considered for a contributed talk.