Sanket Jantre

Unified Probabilistic Neural Architecture and Weight Ensembling Improves Model Robustness

2022 · arXiv (Cornell University)

Robust machine learning models with accurately calibrated uncertainties are crucial for safety-critical applications. Probabilistic machine learning and especially the Bayesian formalism provide a systematic framework to incorporate robustness through the distributional estimates and reason about …

Data-Augmented Few-Shot Neural Emulator for Computer-Model System Identification

2025 · arXiv (Cornell University)

Partial differential equations (PDEs) underpin the modeling of many natural and engineered systems. It can be convenient to express such models as neural PDEs rather than using traditional numerical PDE solvers by replacing part or …