Tetsuya Motokawa's repositories
pytorch-kronecker-factorization
PyTorch Kronecker Factored Approximation of the Hessian
Hessian-analysis-with-tensotflow2.x
Some Hessian based analysis for practical deep models with tensorflow2
Hessian-analysis-with-tensorflow1.x
Hessian spectral analysis with tensorflow1.x
OptimizationNight_20240219
数理最適化: Optimization Night #8 での発表資料のシミュレーションコード
adaptive-hessian-free-optimization
Implementation of Adaptive Hessian-free optimization.
cgds-package
Package for CGD and ACGD optimizers
cpp-intro
Beginner's guide for C++
deep-learning-with-python-notebooks
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
deep-visualization-toolbox
DeepVis Toolbox
DeepnetHessian
Measurements of Three-Level Hierarchical Structure in the Outliers in the Spectrum of Deepnet Hessians (ICML 2019)
fast_adversarial
Code for the CVPR 2019 article "Decoupling Direction and Norm for Efficient Gradient-Based L2 Adversarial Attacks and Defenses"
fisher-information-matrix
PyTorch implementation of FIM and empirical FIM
fmin
Unconstrained function minimization in Javascript
hbp
Hessian backpropagation (HBP): PyTorch extension of backpropagation for block-diagonal curvature matrix approximations
keras
Deep Learning for humans
Numerical-Caluculation
Implementation of numerical algorithms
numerical-tours
Numerical Tours of Signal Processing
pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
pytorch-a2c-ppo-acktr
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO) and Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR).
pytorch-cnn-visualizations
Pytorch implementation of convolutional neural network visualization techniques
pytorch-hessianfree
PyTorch implementation of Hessian Free optimisation
reinforcement-learning-an-introduction
Python Implementation of Reinforcement Learning: An Introduction
stanford-tensorflow-tutorials
This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.
tensorflow
Computation using data flow graphs for scalable machine learning