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Found 5 papers, 1 papers with code
MGARD: A multigrid framework for high-performance, error-controlled data compression and refactoring
We describe MGARD, a software providing MultiGrid Adaptive Reduction for floating-point scientific data on structured and unstructured grids.
Streaming Compression of Scientific Data via weak-SINDy
This feature makes streaming compression algorithms well-suited for scientific data compression, where storing the full data set offline is often infeasible.
Convergence Analysis for Training Stochastic Neural Networks via Stochastic Gradient Descent
In this paper, we carry out numerical analysis to prove convergence of a novel sample-wise back-propagation method for training a class of stochastic neural networks (SNNs).
A Kernel Learning Method for Backward SDE Filter
In this paper, we develop a kernel learning backward SDE filter method to estimate the state of a stochastic dynamical system based on its partial noisy observations.
A Backward SDE Method for Uncertainty Quantification in Deep Learning
We develop a probabilistic machine learning method, which formulates a class of stochastic neural networks by a stochastic optimal control problem.
