sgoldt/gaussian-equiv-2layer

Code and resources for "The Gaussian equivalence of generative models for learning with two-layer neural networks" [https://arxiv.org/abs/2006.14709]

Language: Python - Size: 163 MB - Last synced at: about 1 year ago - Pushed at: about 5 years ago - Stars: 7 - Forks: 1

sgoldt/nn2pp

Utilities to train two-layer neural networks

Language: C++ - Size: 264 KB - Last synced at: about 1 year ago - Pushed at: over 3 years ago - Stars: 4 - Forks: 4

sgoldt/hidden-manifold-model

Tools to train neural networks on structured data sets

Language: C++ - Size: 72.3 KB - Last synced at: about 1 year ago - Pushed at: about 5 years ago - Stars: 8 - Forks: 1

sgoldt/dist_inc_comp

Experiments exploring a distributional simplicity bias in neural networks

Language: Python - Size: 1.35 MB - Last synced at: about 1 year ago - Pushed at: over 2 years ago - Stars: 7 - Forks: 2

sgoldt/pyscm

(Online) learning in two-layer neural networks

Language: Mathematica - Size: 38.1 KB - Last synced at: about 1 year ago - Pushed at: almost 6 years ago - Stars: 5 - Forks: 1

sgoldt/conv_emerge

Code to accompany "Data-driven emergence of convolutional structure in neural networks" [arXiv:2202.00565]

Language: Python - Size: 510 KB - Last synced at: about 1 year ago - Pushed at: over 2 years ago - Stars: 6 - Forks: 2

sgoldt/reconstructing_memories

Code for "Bayesian reconstruction of memories stored in neural networks from their connectivity" https://arxiv.org/abs/2105.07416

Language: Python - Size: 37.1 KB - Last synced at: about 1 year ago - Pushed at: about 4 years ago - Stars: 2 - Forks: 1

sgoldt/deepget

Language: Python - Size: 150 MB - Last synced at: about 1 year ago - Pushed at: over 4 years ago - Stars: 0 - Forks: 0