Jiaqing-ASU

logicnets

m3_learning

Datasets, Tutorials, and Papers for the M3-Learning Research Group

characterizing-pinns-failure-modes

Characterizing possible failure modes in physics-informed neural networks.

PyHessian

PyHessian is a Pytorch library for second-order based analysis and training of Neural Networks

learning-subspaces

Jiaqing-ASU.github.io

loss_landscape_taxonomy

[NeurIPS 2021] code for "Taxonomizing local versus global structure in neural network loss landscapes" https://arxiv.org/abs/2107.11228

onnx-mlir

Representation and Reference Lowering of ONNX Models in MLIR Compiler Infrastructure

loss-landscapes

Approximating neural network loss landscapes in low-dimensional parameter subspaces for PyTorch

Py-ONNX-C-DB

A toolkit that enables users to leverage ONNX-MLIR from python

ml-db-tests

decisiontree-tests

loss-landscape

Code for visualizing the loss landscape of neural nets

ttk

TTK - Topological Data Analysis and Visualization - Source Code

ml-model-tests

AndroidStudio

CSE511-TeamProject

llvm-tests