MadryLab/glm_saga MadryLab/glm_saga

  • Stars
    star
    23
  • Rank 1,016,462 (Top 21 %)
  • Language
    Python
  • License
    MIT License
  • Created almost 4 years ago
  • Updated about 3 years ago
Twitter logo Share LinkedIn logo Share Facebook logo Share
MadryLab/glm_saga
github

MadryLab

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

Minimal, standalone library for solving GLMs in PyTorch

More Repositories

1

robustness

A library for experimenting with, training and evaluating neural networks, with a focus on adversarial robustness.
Jupyter Notebook
905
star
2

mnist_challenge

A challenge to explore adversarial robustness of neural networks on MNIST.
Python
720
star
3

cifar10_challenge

A challenge to explore adversarial robustness of neural networks on CIFAR10.
Python
488
star
4

photoguard

Raising the Cost of Malicious AI-Powered Image Editing
Jupyter Notebook
419
star
5

constructed-datasets

Datasets for the paper "Adversarial Examples are not Bugs, They Are Features"
178
star
6

trak

A fast, effective data attribution method for neural networks in PyTorch
Python
169
star
7

robust_representations

Code for "Learning Perceptually-Aligned Representations via Adversarial Robustness"
Jupyter Notebook
158
star
8

backgrounds_challenge

Python
134
star
9

robustness_applications

Notebooks for reproducing the paper "Computer Vision with a Single (Robust) Classifier"
Jupyter Notebook
125
star
10

implementation-matters

Python
104
star
11

EditingClassifiers

Python
95
star
12

robust-features-code

Code for "Robustness May Be at Odds with Accuracy"
Jupyter Notebook
91
star
13

datamodels-data

Data for "Datamodels: Predicting Predictions with Training Data"
Python
64
star
14

blackbox-bandits

Code for "Prior Convictions: Black-Box Adversarial Attacks with Bandits and Priors"
Python
61
star
15

BREEDS-Benchmarks

Jupyter Notebook
50
star
16

cox

A lightweight experimental logging library
Python
50
star
17

adversarial_spatial

Investigating the robustness of state-of-the-art CNN architectures to simple spatial transformations.
Python
49
star
18

modeldiff

ModelDiff: A Framework for Comparing Learning Algorithms
Jupyter Notebook
44
star
19

failure-directions

Distilling Model Failures as Directions in Latent Space
Jupyter Notebook
42
star
20

smoothed-vit

Certified Patch Robustness via Smoothed Vision Transformers
Python
41
star
21

label-consistent-backdoor-code

Code for "Label-Consistent Backdoor Attacks"
Python
40
star
22

dataset-interfaces

Dataset Interfaces: Diagnosing Model Failures Using Controllable Counterfactual Generation
Jupyter Notebook
39
star
23

DebuggableDeepNetworks

Jupyter Notebook
37
star
24

data-transfer

Python
31
star
25

ImageNetMultiLabel

Fine-grained ImageNet annotations
Jupyter Notebook
28
star
26

relu_stable

Python
26
star
27

spatial-pytorch

Codebase for "Exploring the Landscape of Spatial Robustness" (ICML'19, https://arxiv.org/abs/1712.02779).
Jupyter Notebook
26
star
28

dataset-replication-analysis

Jupyter Notebook
25
star
29

backdoor_data_poisoning

Python
25
star
30

AdvEx_Tutorial

Jupyter Notebook
14
star
31

rethinking-backdoor-attacks

Python
14
star
32

bias-transfer

Python
13
star
33

robustness_lib

Python
12
star
34

journey-TRAK

Code for the paper "The Journey, Not the Destination: How Data Guides Diffusion Models"
Python
12
star
35

datamodels

Python
12
star
36

rla

Residue Level Alignment
Python
12
star
37

copriors

Combining Diverse Feature Priors
Python
8
star
38

missingness

Code for our ICLR 2022 paper "Missingness Bias in Model Debugging"
Jupyter Notebook
5
star
39

fast_l1

Jupyter Notebook
3
star
40

pytorch-lightning-imagenet

Python
3
star
41

post--adv-discussion

HTML
2
star
42

AIaaS_Supply_Chains

Dataset and overview
2
star
43

pytorch-example-imagenet

Python
1
star
44

mnist_challenge_models

1
star
45

robust_model_colab

JavaScript
1
star