Dyad SciML Tutorial: Model Discovery with Universal Differential Equations

Automatic Differentiation is not Efficient on Newton's Method

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

Scientific machine learning and heterogeneous data

Why Floating Point Accuracy Isn't Enough for Stable Algorithms

Physics-informed neural networks without learning boundary conditions!?!?!

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

Automatic differentiation is incorrect on very simple functions??? 😱 😱 😱

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

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

Research Life

Runge-Kutta's 4th order method is not optimal

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

The most commonly used stiff ODE solver isn't A-stable?!?!?

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

SURD: A causal Inference tool for Scientific Discovery

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

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

Constructing custom thermodynamics using deep learning

Machine Learning for Scientific Discovery, with Examples in Fluid Mechanics

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

#mounting the #server #ml #virtualenvironment #deepmind

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

Artificial intelligence for synthetic organic and analytical chemistry

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

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

Model-Agnostic-Predictive Temporal Difference for active control | Tapas Tripura | JHU-IITD SMaRT

Artificial intelligence for synthetic organic and analytical chemistry

Foundation Potentials for Massive Scale Materials Design

AI/ML for Fusion Energy

Machine Learning in Geosciences: Earthquakes, Ice, and XAI

Dhyuti Talk #3 | Rahul Sundar | Universe of PINNs: Variants, Applications and Business implications

Advancing Ecosystem Understanding through Knowledge-Guided Machine Learning