A Python implementation of the Neural Tangent Kernel (jacot et al, 2018)
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Updated
Feb 22, 2021 - Jupyter Notebook
A Python implementation of the Neural Tangent Kernel (jacot et al, 2018)
Understand the spectral bias of deep learning through the study of NTK
Code for paper
Official Code: Trust Your Robots! Predictive Uncertainty Estimation of Neural Networks with Sparse Gaussian Processes
Yale S&DS 432 final project studying lazy training dynamics for differentiable optimization problems
Empirical analysis of the Laplace and neural tangent kernel reproducing kernel Hilbert space (RKHS)
Coursework of MIT 6.S088
Study of the paper 'Neural Thompson Sampling' published in October 2020
Implementation of "Deep Learning in Random Neural Fields: Numerical Experiments via Neural Tangent Kernel"
Implementation of Approximate Smooth Kernel Value Iteration
TF2 Implementation of Physics Informed Neural Networks and Neural Tangent Kernel
Senior Project for Statistics & Data Science at Yale University
TCT: Convexifying Federated Learning using Bootstrapped Neural Tangent Kernels
codebase for "A Theory of the Inductive Bias and Generalization of Kernel Regression and Wide Neural Networks"
Code for "Learnware Reduced Kernel Mean Embedding Specification Based on Neural Tangent Kernel"
We propose a lossless compression algorithm based on the NTK matrix for DNN. The compressed network yields asymptotically the same NTK as the original (dense and unquantized) network, with its weights and activations taking values only in {0, 1, -1} up to scaling.
Code accompanying the paper "On the adaptation of recurrent neural networks for system identification"
A fast, effective data attribution method for neural networks in PyTorch
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.
Official repository of our work "Finding Lottery Tickets in Vision Models via Data-driven Spectral Foresight Pruning" accepted at CVPR 2024
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