2 citations · 2 across the 9 of their papers we have counts for
3 papers · 1 filter
Unveiling Multi-regime Patterns in SciML: Distinct Failure Modes and Regime-specific Optimization
Yuxin Wang, Yuanzhe Hu, Xiaokun Zhong +7
Neural networks trained under different hyperparameter settings can fall into distinct training "regimes," with consistent behavior within regimes and qualitative differences acros…
Landscaper: Understanding Loss Landscapes Through Multi-Dimensional Topological Analysis
Jiaqing Chen, Nicholas Hadler, Tiankai Xie +8
Loss landscapes are a powerful tool for understanding neural network optimization and generalization, yet traditional low-dimensional analyses often miss complex topological featur…
Learning to Discover Iterative Spectral Algorithms
Zihang Liu, Oleg Balabanov, Yaoqing Yang +1
We introduce AutoSpec, a neural network framework for discovering iterative spectral algorithms for large-scale numerical linear algebra and numerical optimization. Our self-superv…