Institute for Pure & Applied Mathematics (IPAM)

Richard Mann - Learning to Disagree - IPAM at UCLA

Daniel Blair - Dynamic Mechanical Phases in Active and Passive Fluids - IPAM at UCLA

Conor Heins - Collective behavior from surprise minimization - IPAM at UCLA

Joshua Tan - Composing games into complex institutions - IPAM at UCLA

Bernard Chazelle - New Tools for Analyzing Collective Behavior - IPAM at UCLA

Iain Couzin - Cognitive collectives - IPAM at UCLA

Collective behavior research is shifting from simple statistical mechanics models toward neurobiological frameworks that account for individual cognition. Traditional models, such as the V-check and Cousin models, rely on explicit alignment rules that lack empirical support in nature. Instead, animal navigation and dec...

Orit Peleg - Emergent Spatiotemporal Patterns in Insect Swarms - IPAM at UCLA

Ahmed El Hady - Mechanistic theory of social foraging - IPAM at UCLA

Vishwesha Guttal - Stochasticity and collective escape responses in moving animal groups

Mauro Maggioni - On exploiting compositional structure: one bit of theory and one application

Josh Tenenbaum - Scaling Intelligence the Human Way - IPAM at UCLA

Pronita Mehrotra - Cognitive Mechanisms That Power Learning and Creativity - IPAM at UCLA

Rupak Majumdar - How to interact when you must - IPAM at UCLA

Una May O Reilly - Adversarial Intelligence in Natural and Artificial Systems - IPAM at UCLA

Swarat Chaudhuri - Abstraction and Evolution with Large Language Models - IPAM at UCLA

Erik Winfree - Equilibrium is inference: lessons from a model of liquid-liquid phase separation

Aishni Parab - Extracting Structured Data from Multi-Modal Input - IPAM at UCLA

Kevin Ellis - Probabilistic Thinking in Language and Code - IPAM at UCLA

Sumit Gulwani - Program Synthesis: Applications, Experiences, and Neuro-Symbolic Techniques

Levi Lelis - Learning Libraries of Programmatic Policies - IPAM at UCLA