12 citations · 42 across the 9 of their papers we have counts for
9 papers
Muscle Anatomy-aware Geometric Deep Learning for sEMG-based Gesture Decoding
Adyasha Dash, Giulia Zappoli, Laya Das +1
Robust and accurate decoding of gesture from non-invasive surface electromyography (sEMG) is important for various applications including spatial computing, healthcare, and enterta…
An Improved Anomaly Detection Model for Automated Inspection of Power Line Insulators
Laya Das, Blazhe Gjorgiev, Giovanni Sansavini
Inspection of insulators is important to ensure reliable operation of the power system. Deep learning is being increasingly exploited to automate the inspection process by leveragi…
There is more to graphs than meets the eye: Learning universal features with self-supervision
Laya Das, Sai Munikoti, Nrushad Joshi +1
We study the problem of learning features through self-supervision that are generalisable to multiple graphs. State-of-the-art graph self-supervision restricts training to only one…
Uncertainty-aware deep learning for digital twin-driven monitoring: Application to fault detection in power lines
Laya Das, Blazhe Gjorgiev, Giovanni Sansavini
Deep neural networks (DNNs) are often coupled with physics-based models or data-driven surrogate models to perform fault detection and health monitoring of systems in the low data…
Object detection-based inspection of power line insulators: Incipient fault detection in the low data-regime
Laya Das, Mohammad Hossein Saadat, Blazhe Gjorgiev +2
Deep learning-based object detection is a powerful approach for detecting faulty insulators in power lines. This involves training an object detection model from scratch, or fine t…
Neural tangent kernel analysis of PINN for advection-diffusion equation
M. H. Saadat, B. Gjorgiev, L. Das +1
Physics-informed neural networks (PINNs) numerically approximate the solution of a partial differential equation (PDE) by incorporating the residual of the PDE along with its initi…
A unified theory of emergent equilibrium phenomena in active and passive matter
Venkat Venkatasubramanian, Abhishek Sivaram, Laya Das
Recent attempts towards a theory of active matter utilize concepts and methods from hydrodynamics, kinetic theory, and non-equilibrium statistical physics. However, such approaches…
Challenges and Opportunities in Deep Reinforcement Learning with Graph Neural Networks: A Comprehensive review of Algorithms and Applications
Sai Munikoti, Deepesh Agarwal, Laya Das +2
Deep reinforcement learning (DRL) has empowered a variety of artificial intelligence fields, including pattern recognition, robotics, recommendation-systems, and gaming. Similarly,…
Robust and Efficient Swarm Communication Topologies for Hostile Environments
Vipul Mann, Abhishek Sivaram, Laya Das +1
Swarm Intelligence-based optimization techniques combine systematic exploration of the search space with information available from neighbors and rely strongly on communication amo…