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cs.LG2026
Beyond Time Induction: Structured Conditional Neural Solvers for Parametric Stochastic-Volatility Pricing
Jose Miguel Lara Rangel, Mixtli Vazquez Mendoza
Physics-informed neural networks provide a flexible framework for learning parametric PDE solution families without labeled data, yet preserving accurate derivatives across heterog…
cs.LG2026
Neural Operator Processes for Probabilistic Operator Learning under Partial Observations
Jose Miguel Lara-Rangel, Serge Guillas
Neural operators learn mappings between function spaces, but are typically developed with dense input-output training fields and fully observed inputs at inference. Many scientific…