4 papers
Harpoon: Generalised Manifold Guidance for Conditional Tabular Diffusion
Aditya Shankar, Yuandou Wang, Rihan Hai +1
Generating tabular data under conditions is critical to applications requiring precise control over the generative process. Existing methods rely on training-time strategies that d…
An Attention-based Feature Memory Design for Energy-Efficient Continual Learning
Yuandou Wang, Filip Gunnarsson, Rihan Hai
Tabular data streams are increasingly prevalent in real-time decision-making across healthcare, finance, and the Internet of Things, often generated and processed on resource-const…
WaveStitch: Flexible and Fast Conditional Time Series Generation with Diffusion Models
Aditya Shankar, Lydia Y. Chen, Arie van Deursen +1
Generating temporal data under conditions is crucial for forecasting, imputation, and generative tasks. Such data often has metadata and partially observed signals that jointly inf…
Share Secrets for Privacy: Confidential Forecasting with Vertical Federated Learning
Aditya Shankar, Jérémie Decouchant, Dimitra Gkorou +2
Vertical federated learning (VFL) is a promising area for time series forecasting in many applications, such as healthcare and manufacturing. Critical challenges to address include…