3 papers
cs.LG2026
GAIA: Geometry-Adaptive Operator Learning for Forward and Inverse Problems
Meenakshi Krishnan, Pranav Pulijala, Ke Chen +2
Operator learning for partial differential equations (PDEs) on arbitrary geometries builds fast neural surrogates for large-scale simulation. Although recent geometry-adaptive neur…
cs.SD2026
Analytical Exploration of Spatial Audio Cues: A Differentiable Multi-Sphere Scattering Model
Siminfar Samakoush Galougah, Pranav Pulijala, Ramani Duraiswami
A primary challenge in developing synthetic spatial hearing systems, particularly underwater, is accurately modeling sound scattering. Biological organisms achieve 3D spatial heari…
cs.LG2024
LookupFFN: Making Transformers Compute-lite for CPU inference
Zhanpeng Zeng, Michael Davies, Pranav Pulijala +2
While GPU clusters are the de facto choice for training large deep neural network (DNN) models today, several reasons including ease of workflow, security and cost have led to effo…