12 citations · 29 across the 14 of their papers we have counts for
5 papers · 1 filter
On the Role of Inductive Bias in Time-Series Pretraining: A Case Study in Learning Generalizable Representations for Clinical Time Series
Sharmita Dey, Diego Paez-Granados
Clinical time-series learning is routinely constrained by small, heterogeneous cohorts and protocol drift, while its downstream use spans both classification (e.g., pathology diagn…
Cross-Modal Diffusion for Biomechanical Dynamical Systems Through Local Manifold Alignment
Sharmita Dey, Sarath Ravindran Nair
We present a mutually aligned diffusion framework for cross-modal biomechanical motion generation, guided by a dynamical systems perspective. By treating each modality, e.g., obser…
Redefining Robot Generalization Through Interactive Intelligence
Sharmita Dey
Recent advances in large-scale machine learning have produced high-capacity foundation models capable of adapting to a broad array of downstream tasks. While such models hold great…
Continual Learning from Simulated Interactions via Multitask Prospective Rehearsal for Bionic Limb Behavior Modeling
Sharmita Dey, Benjamin Paassen, Sarath Ravindran Nair +2
Lower limb amputations and neuromuscular impairments severely restrict mobility, necessitating advancements beyond conventional prosthetics. While motorized bionic limbs show promi…
Enhancing Joint Motion Prediction for Individuals with Limb Loss Through Model Reprogramming
Sharmita Dey, Sarath R. Nair
Mobility impairment caused by limb loss is a significant challenge faced by millions of individuals worldwide. The development of advanced assistive technologies, such as prostheti…