kwang0913's Stars
udlbook/udlbook
Understanding Deep Learning - Simon J.D. Prince
EthicalML/awesome-production-machine-learning
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
IDSIA/sacred
Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
aimhubio/aim
Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
ritchieng/the-incredible-pytorch
The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.
bharathgs/Awesome-pytorch-list
A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.
n2cholas/awesome-jax
JAX - A curated list of resources https://github.com/google/jax
thegregyang/NNspectra
Computing the eigenvalues of Neural Tangent Kernel and Conjugate Kernel (aka NNGP kernel) over the boolean cube
ykasten/Convergence-Rate-NN-Different-Frequencies
maxkvant/LinearizedNNs
cornellius-gp/gpytorch
A highly efficient implementation of Gaussian Processes in PyTorch
tum-pbs/pbdl-book
Welcome to the Physics-based Deep Learning Book (v0.2)
akiilab/random-fourier-features-svm
Implement the Random Fourier Features SVM kernel approximation for Large-Scale Kernel Machines.
qw3rtman/random-feature-maps
Fast Random Kernelized Features: Support Vector Machine Classification for High-Dimensional IDC Dataset
ashishpatel26/Tools-to-Design-or-Visualize-Architecture-of-Neural-Network
Tools to Design or Visualize Architecture of Neural Network
geyang/ffn
Public Repo for the paper "Overcoming The Spectral-Bias of Neural Value Approximation"
MinghuiChen43/awesome-deep-phenomena
A curated list of papers of interesting empirical study and insight on deep learning. Continually updating...
google-deepmind/dks
Multi-framework implementation of Deep Kernel Shaping and Tailored Activation Transformations, which are methods that modify neural network models (and their initializations) to make them easier to train.
james-simon/eigenlearning
codebase for "A Theory of the Inductive Bias and Generalization of Kernel Regression and Wide Neural Networks"
kwignb/RandomNeuralField
Implementation of "Deep Learning in Random Neural Fields: Numerical Experiments via Neural Tangent Kernel"
genglinliu/NTK-study
Understand the spectral bias of deep learning through the study of NTK
392781/neural-laplace
Empirical analysis of the Laplace and neural tangent kernel reproducing kernel Hilbert space (RKHS)
FrankCCCCC/DL_DB_Quick_Note
A collection of papers & notes in deep learning and database.
AlbertDominguez/infinite-width-NNs
Infinite-width neural networks from a practical point of view
TimoFlesch/NeuralTangentKernel
A Python implementation of the Neural Tangent Kernel (jacot et al, 2018)
392781/scikit-ntk
Neural Tangent Kernel (NTK) module for the scikit-learn library
kwignb/NeuralTangentKernel-Papers
Neural Tangent Kernel Papers
rajatvd/NTK
Code for experiments in my blog post on the Neural Tangent Kernel: https://rajatvd.github.io/NTK
insuhan/ntk-sketch-rf
Python implementation of Scaling Neural Tangent Kernels via Sketching and Random Features
damaru2/ntk
NTK reading group