5 papers
Spatial self-organization driven by temporal noise
Satyam Anand, Guanming Zhang, Stefano Martiniani
The counterintuitive emergence of order from noise is a central phenomenon in science, ranging from pattern formation and synchronization to order-by-disorder in frustrated systems…
Contrastive Self-Supervised Learning As Neural Manifold Packing
Guanming Zhang, David J. Heeger, Stefano Martiniani
Contrastive self-supervised learning based on point-wise comparisons has been widely studied for vision tasks. In the visual cortex of the brain, neuronal responses to distinct sti…
A unifying approach to self-organizing systems interacting via conservation laws
Frank Barrows, Guanming Zhang, Satyam Anand +5
We present a unified framework for embedding and analyzing dynamical systems using generalized projection operators rooted in local conservation laws. By representing physical, bio…
Emergent universal long-range structure in random-organizing systems
Satyam Anand, Guanming Zhang, Stefano Martiniani
Self-organization through noisy interactions is ubiquitous across physics, mathematics, and machine learning, yet how long-range structure emerges from local noisy dynamics remains…
Absorbing state dynamics of stochastic gradient descent
Guanming Zhang, Stefano Martiniani
Stochastic gradient descent (SGD) is a fundamental tool for training deep neural networks across a variety of tasks. In self-supervised learning, different input categories map to…