Stathi Fotiadis

According to our database, Stathi Fotiadis authored at least 12 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Stochastic Flow Matching for Resolving Small-Scale Physics.

Stathi Fotiadis, Noah D. Brenowitz, Tomas Geffner, Yair Cohen, Michael S. Pritchard, Arash Vahdat, Morteza Mardani

CoRR, 2024

2023

Score Normalization for a Faster Diffusion Exponential Integrator Sampler.

Guoxuan Xia, Duolikun Danier, Ayan Das, Stathi Fotiadis, Farhang Nabiei, Ushnish Sengupta, Alberto Bernacchia

CoRR, 2023

Disentangled Generative Models for Robust Prediction of System Dynamics.

Stathi Fotiadis, Mario Lino Valencia, Shunlong Hu, Stef Garasto, Chris D. Cantwell, Anil Anthony Bharath

Proceedings of the International Conference on Machine Learning, 2023

Image generation with shortest path diffusion.

Ayan Das, Stathi Fotiadis, Anil Batra, Farhang Nabiei, Fengting Liao, Sattar Vakili, Da-Shan Shiu, Alberto Bernacchia

Proceedings of the International Conference on Machine Learning, 2023

Fisher-Legendre (FishLeg) optimization of deep neural networks.

Jezabel R. Garcia, Federica Freddi, Stathi Fotiadis, Maolin Li, Sattar Vakili, Alberto Bernacchia, Guillaume Hennequin

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Towards Fast Simulation of Environmental Fluid Mechanics with Multi-Scale Graph Neural Networks.

Mario Lino, Stathi Fotiadis, Anil A. Bharath, Chris D. Cantwell

CoRR, 2022

REMuS-GNN: A Rotation-Equivariant Model for Simulating Continuum Dynamics.

Mario Lino, Stathi Fotiadis, Anil A. Bharath, Chris D. Cantwell

Proceedings of the Topological, 2022

2021

Disentangling ODE parameters from dynamics in VAEs.

Stathi Fotiadis, Mario Lino, Chris D. Cantwell, Anil A. Bharath

CoRR, 2021

Simulating Continuum Mechanics with Multi-Scale Graph Neural Networks.

Mario Lino, Chris D. Cantwell, Anil A. Bharath, Stathi Fotiadis

CoRR, 2021

2020

Simulating Surface Wave Dynamics with Convolutional Networks.

Mario Lino Valencia, Chris D. Cantwell, Stathi Fotiadis, Eduardo Pignatelli, Anil A. Bharath

CoRR, 2020

Comparing recurrent and convolutional neural networks for predicting wave propagation.

Stathi Fotiadis, Eduardo Pignatelli, Mario Lino Valencia, Chris D. Cantwell, Amos J. Storkey, Anil A. Bharath

CoRR, 2020

2019

An Empirical Evaluation of Adversarial Robustness under Transfer Learning.

Todor Davchev, Timos Korres, Stathi Fotiadis, Nick Antonopoulos, Subramanian Ramamoorthy

CoRR, 2019