Zeyuan publishes on NeurIPS 2026

Our paper entitled Theory Guided and Interpretable Neural Operator Design for Partial Differential Equation Learning is accpeted by NeurIPS 2026. This work, which presents a new paradigm for designing mathematically grounded neural operator for partial differential equation learning, marks the first publication from Oklahoma schools in this top venue for AI/machine learning research!