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cs.LG2026
APIC: Amortized Physics-Informed Calibration using Neural Processes
Aishwarya Venkataramanan, Sai Karthikeya Vemuri, Joachim Denzler
Physics models are inherently imperfect due to misspecified or missing mechanisms, resulting in systematic discrepancies between model predictions and real-world observations. The…
cs.LG2025
Uncertainty-aware Physics-informed Neural Networks for Robust CARS-to-Raman Signal Reconstruction
Aishwarya Venkataramanan, Sai Karthikeya Vemuri, Adithya Ashok Chalain Valapil +1
Coherent anti-Stokes Raman scattering (CARS) spectroscopy is a powerful and rapid technique widely used in medicine, material science, and chemical analyses. However, its effective…
cs.LG2025
Distance-informed Neural Processes
Aishwarya Venkataramanan, Joachim Denzler
We propose the Distance-informed Neural Process (DNP), a novel variant of Neural Processes that improves uncertainty estimation by combining global and distance-aware local latent…