Publications (16)
Taming the Memory Beast: Strategies for Reliable ML Training on Kubernetes
Jaideep Ray
Kubernetes offers a powerful orchestration platform for machine learning training, but memory management can be challenging due to specialized needs and resource constraints. This…
Daily Forecasting of New Cases for Regional Epidemics of Coronavirus Disease 2019 with Bayesian Uncertainty Quantification
Yen Ting Lin, Jacob Neumann, Ely Miller +7
To increase situational awareness and support evidence-based policy-making, we formulated two types of mathematical models for COVID-19 transmission within a regional population. O…
Decreasing the temporal complexity for nonlinear, implicit reduced-order models by forecasting
Kevin Carlberg, Jaideep Ray, Bart van Bloemen Waanders
Implicit numerical integration of nonlinear ODEs requires solving a system of nonlinear algebraic equations at each time step. Each of these systems is often solved by a Newton-lik…
The Constraint Tax: Measuring Validity-Correctness Tradeoffs in Structured Outputs for Small Language Models
Jaideep Ray
Production LLM systems increasingly require machine-readable outputs: JSON objects, typed traces, regex-constrained fields, and tool-call schemas. This paper targets on-device and…
Projection-based model reduction of dynamical systems using space-time subspace and machine learning
Chi Hoang, Kenny Chowdhary, Kookjin Lee +1
This paper considers the creation of parametric surrogate models for applications in science and engineering where the goal is to predict high-dimensional spatiotemporal output qua…
Trust-Aware Multimodal Data Fusion for Yield Estimation: A Case Study of the 2020 Beirut Explosion
Lekha Patel, Craig Ulmer, Stephen J. Verzi +4
The estimation of explosive yield from heterogeneous observational data presents fundamental challenges in inverse problems, particularly when combining traditional physical measur…