2 citations · 4 across the 6 of their papers we have counts for
6 papers
LieStoNet: Learning Lie Symmetries from Spatiotemporal Data for Stochastic Dynamical Systems
Shida Liu, Abhishek Gupta, Sumit Sinha +1
Symmetry is central to modern machine learning and physics: invariances and equivariances improve sample efficiency, robustness, and out-of-distribution generalization, while symme…
Generative optimal transport via forward-backward HJB matching
Haiqian Yang, Vishaal Krishnan, Sumit Sinha +1
Controlling the evolution of a many-body stochastic system from a disordered reference state to a structured target ensemble, characterized empirically through samples, arises natu…
Morphological instability of an invasive active-passive interface
Sumit Sinha, Haiqian Yang, L Mahadevan
Morphological instabilities of growing tissues that impinge on passive materials are typical of invasive cancers. To explain these instabilities in experiments on breast epithelial…
Stigmergic optimal transport
Vishaal Krishnan, L. Mahadevan
Efficient navigation in swarms often relies on the emergence of decentralized approaches that minimize traversal time or energy. Stigmergy, where agents modify a shared environment…
Hamiltonian bridge: A physics-driven generative framework for targeted pattern control
Vishaal Krishnan, Sumit Sinha, L. Mahadevan
Patterns arise spontaneously in a range of systems spanning the sciences, and their study typically focuses on mechanisms to understand their evolution in space-time. Increasingly,…
Optimal control of interacting active particles on complex landscapes
Sumit Sinha, Vishaal Krishnan, L Mahadevan
Active many-body systems composed of many interacting degrees of freedom often operate out of equilibrium, giving rise to non-trivial emergent behaviors which can be functional in…