no code implementations • 15 Oct 2021 • Lokesh Boominathan, Xaq Pitkow
We show that there is a non-monotonic dependence of optimal feedback gain as a function of both the computational parameters and the world dynamics, leading to phase transitions in whether feedback provides any utility in optimal inference under computational constraints.
no code implementations • 9 May 2018 • Lokesh Boominathan, Mayug Maniparambil, Honey Gupta, Rahul Baburajan, Kaushik Mitra
For the low overlap case we show that a supervised deep learning technique using an autoencoder generator is a good choice for solving the Fourier ptychography problem.
no code implementations • 17 Nov 2016 • Lokesh Boominathan, Suraj Srinivas, R. Venkatesh Babu
This is inspired by the neuro-scientific concept of mental rotation, which humans use to compare pairs of rotated objects.
2 code implementations • 22 Aug 2016 • Lokesh Boominathan, Srinivas S. S. Kruthiventi, R. Venkatesh Babu
Our work proposes a novel deep learning framework for estimating crowd density from static images of highly dense crowds.