4 citations · 4 across the 8 of their papers we have counts for
6 papers · 1 filter
FoilDiff: A Hybrid Transformer Backbone for Diffusion-based Modelling of 2D Airfoil Flow Fields
Kenechukwu Ogbuagu, Sepehr Maleki, Giuseppe Bruni +1
The accurate prediction of flow fields around airfoils is crucial for aerodynamic design and optimisation. Computational Fluid Dynamics (CFD) models are effective but computational…
Diffusion Models: A Mathematical Introduction
Sepehr Maleki, Negar Pourmoazemi
We present a concise, self-contained derivation of diffusion-based generative models. Starting from basic properties of Gaussian distributions (densities, quadratic expectations, r…
Pi-transformer: A prior-informed dual-attention model for multivariate time-series anomaly detection
Sepehr Maleki, Negar Pourmoazemi
Anomalies in multivariate time series often arise from temporal context and cross-channel coordination rather than isolated outliers. We present Pi-Transformer (Prior-Informed Tran…
Physics-Informed Neural Networks for Industrial Gas Turbines: Recent Trends, Advancements and Challenges
Afila Ajithkumar Sophiya, Sepehr Maleki, Giuseppe Bruni +1
Physics-Informed Neural Networks (PINNs) have emerged as a promising computational framework for solving differential equations by integrating deep learning with physical constrain…
A comprehensive analysis of PINNs: Variants, Applications, and Challenges
Afila Ajithkumar Sophiya, Akarsh K Nair, Sepehr Maleki +1
Physics Informed Neural Networks (PINNs) have been emerging as a powerful computational tool for solving differential equations. However, the applicability of these models is still…
C(NN)FD -- Deep Learning Modelling of Multi-Stage Axial Compressors Aerodynamics
Giuseppe Bruni, Sepehr Maleki, Senthil K Krishnababu
The field of scientific machine learning and its applications to numerical analyses such as CFD has recently experienced a surge in interest. While its viability has been demonstra…