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Mike Kirby

2 accepted papers

2024

Functional Bayesian Tucker Decomposition for Continuous-indexed Tensor Data

ICLR 2024poster

Tucker decomposition is a powerful tensor model to handle multi-aspect data. It demonstrates the low-rank property by decomposing the grid-structured data as interactions between a core tensor and a set of object representations (factors). A fundamental assumption of such decomposition is that ther…

2024

Solving High Frequency and Multi-Scale PDEs with Gaussian Processes

ICLR 2024poster

Machine learning based solvers have garnered much attention in physical simulation and scientific computing, with a prominent example, physics-informed neural networks (PINNs). However, PINNs often struggle to solve high-frequency and multi-scale PDEs, which can be due to spectral bias during neural…