6 papers
Learning Population-Level Dynamics through a Latent Fokker--Planck Model and Discrepancy Transport Maps
Chengyang Huang, Krishna Garikipati
Many scientific and engineering systems are observed as time-indexed probability distributions whose governing dynamics are unknown and whose individual trajectories are unavailabl…
Bayesian Variational System Identification with Weak-Form Residual Likelihoods
Chengyang Huang, Siddhartha Srivastava, Krishna Garikipati +1
We consider system identification for discovering parameterized operators in governing partial differential equations (PDEs) from noisy spatiotemporal data. Building on variational…
CMAG: Concept-Scaffolded Retrieval for Marketplace Avatar Generation
Rajeev Goel, Jason Ding, Phani Harish Wajjala +3
Metaverse platforms rely on creator-driven marketplaces where avatars are assembled from discrete, taxonomy-labeled 3D assets (e.g., tops, bottoms, shoes, accessories) under strict…
Constitutive parameter inference using physics-based data-driven modeling in full volume datasets of intact and torn rotator cuff tendons
Carla Nathaly VillacÃs Núñez, Siddhartha Srivastava, Ulrich Scheven +3
In this work, we characterized the material properties of an animal model of the rotator cuff tendon using full volume datasets of both its intact and injured states by capturing i…
Inference of phase field fracture models
Elizabeth Livingston, Siddhartha Srivastava, Jamie Holber +2
The phase field approach to modeling fracture uses a diffuse damage field to represent a crack. This addresses the singularities that arise at the crack tip in computations with sh…
AI-University: An LLM-based platform for instructional alignment to scientific classrooms
Mostafa Faghih Shojaei, Rahul Gulati, Benjamin A. Jasperson +5
We introduce AI University (AI-U), a flexible framework for AI-driven course content delivery that adapts to instructors' teaching styles. At its core, AI-U fine-tunes a large lang…