jfc43

robust-ood-detection

Robust Out-of-distribution Detection in Neural Networks

informative-outlier-mining

We propose a theoretically motivated method, Adversarial Training with informative Outlier Mining (ATOM), which improves the robustness of OOD detection to various types of adversarial OOD inputs and establishes state-of-the-art performance.

robust-attribution-regularization

Robust Attribution Regularization

self-training-ensembles

Propose a principled and practically effective framework for unsupervised accuracy estimation and error detection tasks with theoretical analysis and state-of-the-art performance.

advex

pixel-discretization

Pixel discretization defense against adversarial attacks

eval-transductive-robustness

Exploring evaluating the adversarial robustness of transductive-learning based defenses.

stratified-adv-rej

Study adversarially-robust classification with rejection where rejection has cost monotonically non-increasing in the perturbation magnitude, and propose a novel defense method with strong performance.

google-research

Google AI Research

armory

ARMORY Adversarial Robustness Evaluation Test Bed

armory-example

Example external repository for interacting with armory.

DataLoaders_DALI

PyTorch DataLoaders implemented with DALI for accelerating image preprocessing

dent

Fighting Gradients with Gradients: Dynamic Defenses against Adversarial Attacks

Low-Precision-SGD-and-Tree-Boosting

Project for Course CS 744 Big Data System

caffe

Caffe: a fast open framework for deep learning.

cifar10_challenge

A challenge to explore adversarial robustness of neural networks on CIFAR10.

DenseNet

Densely Connected Convolutional Networks, In CVPR 2017 (Best Paper Award).

fcn.berkeleyvision.org

Fully Convolutional Networks for Semantic Segmentation by Jonathan Long*, Evan Shelhamer*, and Trevor Darrell. CVPR 2015 and PAMI 2016.

go_moku

go_moku AI

InterpretationFragility

Interpretation of Neural Network is Fragile

jfc43.github.io

LightGBM

A fast, distributed, high performance gradient boosting (GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks. It is under the umbrella of the DMTK(http://github.com/microsoft/dmtk) project of Microsoft.

lottery-ticket-hypothesis

A reimplementation of "The Lottery Ticket Hypothesis" (Frankle and Carbin) on MNIST.

marvin

Marvin: A Minimalist GPU-only N-Dimensional ConvNets Framework

MNC

Instance-aware Semantic Segmentation via Multi-task Network Cascades

pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

releasing-research-code

Tips for releasing research code in Machine Learning (with official NeurIPS 2020 recommendations)

robust-attribution-regularization-1

shifts

This repository contains data readers and examples for the three tracks of the Shifts Dataset and the Shifts Challenge.

Speaker

app