Dyad SciML Tutorial: Model Discovery with Universal Differential Equations

JuliaSim FMU Accelerator App: Digital Twin Generation using Scientific Machine Learning (SciML)

Industrial Grade Scientific Machine Learning: Challenges and Opportunities - Santi Adavani

From Local to Nonlocal Models in Continuum Mechanics: Role of SciML | Dr. N. Bouklas |JHU-IITD SMaRT

Generating a Coffee Cup Thermal Model from a Schematic with Dyad's Agentic AI

Research Life

Diffusion Models for Scientific Machine Learning | Dr. Agnimitra Dasgupta | JHU-IITD SMaRT Seminar

Multi-Fidelity Machine Learning for Uncertainty Quantification | Dr. S. De | JHU-IITD SMaRT Seminar

Challenges of groundwater simulation & opportunities for terrestrial national-scale hydro-modeling

#mounting the #server #ml #virtualenvironment #deepmind

SURD: A causal Inference tool for Scientific Discovery

160x speed up in Crystal Plasticity Finite Element Method??

ML-Driven Prediction & Design for Material Systems|Dr. Sathiskumar Ponnusami|JHU-IITD SMaRT Seminar

How To Know What You Don't Know - Penn Grad Talks 2025 Audience Choice Winner

Constructing custom thermodynamics using deep learning

Foundation Potentials for Massive Scale Materials Design

Machine Learning for Scientific Discovery, with Examples in Fluid Mechanics

Differentiable Programming for Data-driven Modeling, Optimization, and Control

Differentiable Physics for Scientific Discovery | Dr. Romit Maulik | JHU-IITD SMaRT Seminar

Neuroscience-Inspired Deep Learning for Computational Mechanics | S. Garg | JHU-IITD SMaRT Seminar

Dhyuti WalkThrough #1 | #PINNs, inverse problems and 1D analogs of real life examples | Rahul Sundar

Large Datasets in Computational Mechanics & Mechanobiology | Dr. Emma Lejeune | JHU-IITD SMaRT