87 citations · 259 across the 22 of their papers we have counts for
3 papers · 1 filter
A physics-informed search for metric solutions to Ricci flow, their embeddings, and visualisation
Aarjav Jain, Challenger Mishra, Pietro Liò
Neural networks with PDEs embedded in their loss functions (physics-informed neural networks) are employed as a function approximators to find solutions to the Ricci flow (a curvat…
Machine Learned Calabi-Yau Metrics and Curvature
Per Berglund, Giorgi Butbaia, Tristan Hübsch +4
Finding Ricci-flat (Calabi-Yau) metrics is a long standing problem in geometry with deep implications for string theory and phenomenology. A new attack on this problem uses neural…
Machine Learning for Optical Motion Capture-driven Musculoskeletal Modelling from Inertial Motion Capture Data
Abhishek Dasgupta, Rahul Sharma, Challenger Mishra +1
Marker-based Optical Motion Capture (OMC) systems and associated musculoskeletal (MSK) modelling predictions offer non-invasively obtainable insights into in vivo joint and muscle…