63 citations · 63 across the 2 of their papers we have counts for
4 papers
On the Entropy Formula for Real, Complex, and Quaternionic Deep Linear Networks
Luis Contreras, Marco Nahas, Tejas Kotwal
We extend the entropy formula of Menon and Yu for the real Deep Linear Network (DLN) to its complex and quaternionic analogues, obtaining a unified formula for DLNs over $\mathbb{R…
From Ticks to Flows: Dynamics of Neural Reinforcement Learning in Continuous Environments
Saket Tiwari, Tejas Kotwal, George Konidaris
We present a novel theoretical framework for deep reinforcement learning (RL) in continuous environments by modeling the problem as a continuous-time stochastic process, drawing on…
Entropic Regularization in the Deep Linear Network
Alan Chen, Tejas Kotwal, Govind Menon
We study regularization for the deep linear network (DLN) using the entropy formula introduced in arXiv:2509.09088. The equilibria and gradient flow of the free energy on the Riema…
Connecting the Kuramoto Model and the Chimera State
Tejas Kotwal, Xin Jiang, Daniel M. Abrams
Since its discovery in 2002, the chimera state has frequently been described as a counter-intuitive, puzzling phenomenon. The Kuramoto model, in contrast, has become a celebrated p…