4 papers
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…
Saccadic Vision for Fine-Grained Visual Classification
Johann Schmidt, Sebastian Stober, Joachim Denzler +1
Fine-grained visual classification (FGVC) requires distinguishing between visually similar categories through subtle, localized features - a task that remains challenging due to hi…
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…
Probabilistic Embeddings for Frozen Vision-Language Models: Uncertainty Quantification with Gaussian Process Latent Variable Models
Aishwarya Venkataramanan, Paul Bodesheim, Joachim Denzler
Vision-Language Models (VLMs) learn joint representations by mapping images and text into a shared latent space. However, recent research highlights that deterministic embeddings f…