sungyoon-lee

sungyoon-lee's Stars

• wronnyhuang/gen-viz

  Code for the paper "Understanding Generalization through Visualizations"

  Language:Python607

• locuslab/edge-of-stability

  Language:Python5919

• locuslab/robust_overfitting

  Language:Python15329

• amirgholami/HessianFlow

  Language:Python8115

• amirgholami/PyHessian

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

  Language:Jupyter Notebook678118

• AnonymousNIPS2019/DeepnetHessian

  The Full Spectrum of Deepnet Hessians at Scale: Dynamics with SGD Training and Sample Size

  Language:Jupyter Notebook173

• google/spectral-density

  Hessian spectral density estimation in TF and Jax

  Language:Python11228

• csdongxian/AWP

  Codes for NeurIPS 2020 paper "Adversarial Weight Perturbation Helps Robust Generalization"

  Language:Python17020

• Luolc/AdaBound

  An optimizer that trains as fast as Adam and as good as SGD.

  Language:Python2.9k330

• pytorch/contrib

  Implementations of ideas from recent papers

  Language:Python39142

• liuchen11/AdversaryLossLandscape

  On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them [NeurIPS 2020]

  Language:Python355

• jh-jeong/smoothing-consistency

  Code for the paper "Consistency Regularization for Certified Robustness of Smoothed Classifiers" (NeurIPS 2020)

  Language:Python333

• sjhwang82/AdvancedML

  Reading list for the Advanced Machine Learning Course

  36670

• labmlai/annotated_deep_learning_paper_implementations

  🧑‍🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

  Language:Python54.5k5.6k

• sungyoon-lee/SVC

  Language:Python1

• sungyoon-lee/bcp

  [NeurIPS 2020] Lipschitz-Certifiable Training with a Tight Outer Bound | BCP (Box Constraint Propagation) | ⚡💪🛡️

  Language:Jupyter Notebook61

• fra31/auto-attack

  Code relative to "Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks"

  Language:Python646112

• terryum/awesome-deep-learning-papers

  The most cited deep learning papers

  Language:TeX25.4k4.5k

• ageron/handson-ml2

  A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

  Language:Jupyter Notebook27.8k12.7k

• max-andr/cross-lipschitz

  Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation [NeurIPS 2017]

  Language:Python183

• locuslab/smoothing

  Provable adversarial robustness at ImageNet scale

  Language:Python36175

• bmsookim/wide-resnet.pytorch

  Best CIFAR-10, CIFAR-100 results with wide-residual networks using PyTorch

  Language:Python460129

• szagoruyko/wide-residual-networks

  3.8% and 18.3% on CIFAR-10 and CIFAR-100

  Language:Lua1.3k293

• mahyarnajibi/FreeAdversarialTraining

  PyTorch Implementation of Adversarial Training for Free!

  Language:Python23841

• BorealisAI/advertorch

  A Toolbox for Adversarial Robustness Research

  Language:Jupyter Notebook1.3k196

• Harry24k/adversarial-attacks-pytorch

  PyTorch implementation of adversarial attacks [torchattacks]

  Language:Python1.9k348

• chbrian/awesome-adversarial-examples-dl

  A curated list of awesome resources for adversarial examples in deep learning

  26156

• P2333/Papers-of-Robust-ML

  Related papers for robust machine learning

  56455

• JavierAntoran/Bayesian-Neural-Networks

  Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

  Language:Jupyter Notebook1.8k305

• kumar-shridhar/PyTorch-BayesianCNN

  Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.

  Language:Python1.4k324