L. Das

发表

Neural tangent kernel analysis of PINN for advection-diffusion equation

G. Sansavini, M. Saadat, B. Gjorgiev, 2022, 2211.11716.

Hidden representations in deep neural networks: Part 2. Regression problems

Laya Das, Venkat Venkatasubramanian, Abhishek Sivaram, 2020, Comput. Chem. Eng..

Challenges and Opportunities in Deep Reinforcement Learning with Graph Neural Networks: A Comprehensive review of Algorithms and Applications

M. Halappanavar, B. Natarajan, Sai Munikoti, 2022, IEEE transactions on neural networks and learning systems.

A unified theory of emergent equilibrium phenomena in active and passive matter

V. Venkatasubramanian, Laya Das, A. Sivaram, 2022, Comput. Chem. Eng..

Uncertainty-aware deep learning for digital twin-driven monitoring: Application to fault detection in power lines

G. Sansavini, B. Gjorgiev, L. Das, 2023, ArXiv.

Simulation-driven deep learning for locating faulty insulators in a power line

G. Sansavini, B. Gjorgiev, L. Das, 2022, Reliability Engineering & System Safety.

Object detection-based inspection of power line insulators: Incipient fault detection in the low data-regime

G. Sansavini, M. Saadat, B. Gjorgiev, 2022, ArXiv.

There is more to graphs than meets the eye: Learning universal features with self-supervision

M. Halappanavar, Sai Munikoti, L. Das, 2023, ArXiv.

Robust and Efficient Swarm Communication Topologies for Hostile Environments

V. Venkatasubramanian, Vipul Mann, Laya Das, 2020, Swarm Evol. Comput..

Hidden representations in deep neural networks: Part 1. Classification problems

Venkat Venkatasubramanian, Laya Das, Abhishek Sivaram, 2020, Comput. Chem. Eng..