no code implementations • 21 Aug 2023 • Gautam Sreekumar, Vishnu Naresh Boddeti
Spurious correlations occur when a model learns unreliable features from the data and are a well-known drawback of data-driven learning.
no code implementations • 3 Aug 2023 • Vishnu Naresh Boddeti, Gautam Sreekumar, Arun Ross
Our capacity estimates indicate that (a) under ArcFace representation at a false acceptance rate (FAR) of 0. 1%, StyleGAN3 and DCFace have a capacity upper bound of $1. 43\times10^6$ and $1. 190\times10^4$, respectively; (b) the capacity reduces drastically as we lower the desired FAR with an estimate of $1. 796\times10^4$ and $562$ at FAR of 1% and 10%, respectively, for StyleGAN3; (c) there is no discernible disparity in the capacity w. r. t gender; and (d) for some generative models, there is an appreciable disparity in the capacity w. r. t age.
no code implementations • 19 Dec 2022 • Hamed Bolandi, Gautam Sreekumar, Xuyang Li, Nizar Lajnef, Vishnu Naresh Boddeti
Therefore, to reduce computational cost while preserving accuracy, a deep learning model, Neuro-DynaStress, is proposed to predict the entire sequence of stress distribution based on finite element simulations using a partial differential equation (PDE) solver.
no code implementations • 28 Nov 2022 • Hamed Bolandi, Gautam Sreekumar, Xuyang Li, Nizar Lajnef, Vishnu Naresh Boddeti
Therefore, to reduce computational cost while maintaining accuracy, a Physics Informed Neural Network (PINN), PINN-Stress model, is proposed to predict the entire sequence of stress distribution based on Finite Element simulations using a partial differential equation (PDE) solver.
2 code implementations • 12 May 2020 • Zhichao Lu, Gautam Sreekumar, Erik Goodman, Wolfgang Banzhaf, Kalyanmoy Deb, Vishnu Naresh Boddeti
At the same time, the architecture search and transfer is orders of magnitude more efficient than existing NAS methods.
Ranked #1 on Neural Architecture Search on STL-10
Fine-Grained Image Classification Neural Architecture Search +1