8 papers · 1 filter
GNBAN: Graph Neural Basis Attention Networks for Long-Horizon Forecasting over Large Entity Sets
Janak M. Patel, Anirudh Deodhar, Dagnachew Birru
Demand forecasting at the bottom of a retail hierarchy requires predicting tens of thousands of correlated long-horizon series across products, stores, and regions. Modern systems…
State of Health Estimation of Batteries Using a Time-Informed Dynamic Sequence-Inverted Transformer
Janak M. Patel, Milad Ramezankhani, Anirudh Deodhar +1
The rapid adoption of battery-powered vehicles and energy storage systems over the past decade has made battery health monitoring increasingly critical. Batteries play a central ro…
DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting
Owais Ahmad, Milad Ramezankhani, Anirudh Deodhar
Accurate long-term traffic forecasting remains a critical challenge in intelligent transportation systems, particularly when predicting high-frequency traffic phenomena such as sho…
Leveraging Knowledge Graphs and LLM Reasoning to Identify Operational Bottlenecks for Warehouse Planning Assistance
Rishi Parekh, Saisubramaniam Gopalakrishnan, Zishan Ahmad +1
Analyzing large, complex output datasets from Discrete Event Simulations (DES) of warehouse operations to identify bottlenecks and inefficiencies is a critical yet challenging task…
GITO: Graph-Informed Transformer Operator for Learning Complex Partial Differential Equations
Milad Ramezankhani, Janak M. Patel, Anirudh Deodhar +1
We present a novel graph-informed transformer operator (GITO) architecture for learning complex partial differential equation systems defined on irregular geometries and non-unifor…
Accelerated Gradient-based Design Optimization Via Differentiable Physics-Informed Neural Operator: A Composites Autoclave Processing Case Study
Janak M. Patel, Milad Ramezankhani, Anirudh Deodhar +1
Simulation and optimization are crucial for advancing the engineering design of complex systems and processes. Traditional optimization methods require substantial computational ti…