Tensor networks enable tunable, objective compression of 1D fluid data with lossless reconstruction at high bond dimension and efficient in-compressed-space operations like periodic convolution.
hub Mixed citations
Real-time Bayesian inference at extreme scale: A digital twin for tsunami early warning applied to the Cascadia subduction zone
Mixed citation behavior. Most common role is background (60%).
14
Pith papers citing it
Background
60% of classified citations
hub tools
citation-role summary
background 3
dataset 1
method 1
citation-polarity summary
years
2026 14representative citing papers
AtomWorld enables the first direct atomistic simulation of RPV steel at year-and-meter scales, handling ten-quintillion-atom systems and simulating one service year in 1.71 days with 92-97% scaling efficiency on leadership supercomputers.
FP64 tensor cores accelerate high-order finite-element kernels in MFEM by up to 2x with 83% energy gains and near-perfect weak scaling on exascale hardware.
MALOQ introduces a scalable SO(2)-equivariant ML framework with custom kernels and edge-wise graph distribution for predicting large-scale quantum transport operators.
Fused Tensor Core kernels for Ozaki Schemes I and II achieve up to 83% of INT8 peak throughput and outperform cuBLAS TF32 and ZGEMM on large matrices at comparable accuracy.
A finite-element variational inference method delivers full-covariance Bayesian field reconstruction at dimensions exceeding 400,000 for 3D porous media flow using sparse precision parameterization from SPDE priors.
A new overdensity-conditioned emulator trained on small subvolumes from Quijote recovers the global halo mass function via integration over the overdensity distribution at 0.026% of the simulation cost.
A reformulation of Bayesian OED as dense matrix subset selection plus a pipelined Schur-complement greedy algorithm on hundreds of GPUs enables optimization of 175-sensor networks for billion-degree-of-freedom tsunami models with near-perfect scaling.
A dynamic load balancer for UM-Bridge achieves near-millisecond average node idle time on heterogeneous tsunami simulation workloads in Bayesian inversion without prior workload assumptions.
SME-aware kernel and hybrid execution optimizations for SPECFEM3D on LX2 ARM processors deliver 4-6x speedup and shift the favorable (h,p) operating point to higher orders along the dispersion-based iso-accuracy frontier.
A clustering-aware correction algorithm using spatial partitioning and projected gradient descent preserves single-linkage clusters in lossy-compressed particle data while keeping competitive compression ratios.
The quatrex quantum transport solver achieves up to 51% higher throughput using low-precision formats while maintaining accuracy on realistic semiconductor systems.
Introduces a scalable AI skill framework for autonomous microkinetics discovery that automates workflows and evaluates surrogate reliability.