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车人王/SpringBoot-Learning forked from 程序猿DD/SpringBoot-Learning

Spring Boot基础教程，Spring Boot 2.x版本连载中！！！

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车人王/regnet

Pytorch implementation of network design paradigm described in the paper "Designing Network Design Spaces"

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车人王/vega

AutoML tools chain

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车人王/m_testing_adversatial_sample

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车人王/DEBAR

This repository contains the implementation and the evaluation of our ESEC/FSE 2020 paper: Detecting Numerical Bugs in Neural Network Architectures.

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车人王/dissect

Code for the Proceedings of the National Academy of Sciences 2020 article, "Understanding the Role of Individual Units in a Deep Neural Network"

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车人王/HFC

Implementation for the paper (CVPR Oral): High Frequency Component Helps Explain the Generalization of Convolutional Neural Networks

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车人王/AIX360

Interpretability and explainability of data and machine learning models

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车人王/graph2nn

code for paper "Graph Structure of Neural Networks"

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车人王/AT-CNN

Project page for our paper: Interpreting Adversarially Trained Convolutional Neural Networks

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车人王/Proper-Interpretability

Codes for reproducing the experimental results in "Proper Network Interpretability Helps Adversarial Robustness in Classification", published at ICML 2020

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车人王/Bayesian-Adversarial-Learning

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车人王/Automold--Road-Augmentation-Library

This library augments road images to introduce various real world scenarios that pose challenges for training neural networks of Autonomous vehicles. Automold is created to train CNNs in specific weather and road conditions.

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车人王/Foggy-CycleGAN

Code for MSc Thesis: Simulating Weather Conditions on Digital Images, uses a modified CycleGAN model to synthesize fog on clear images

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车人王/forgery_localization_HLED

Implementation of "Hybrid LSTM and Encoder-Decoder Architecture for Detection of Image Forgeries" paper.

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车人王/advml-traffic-sign

Code for the 'DARTS: Deceiving Autonomous Cars with Toxic Signs' paper

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车人王/DeepConcolic

Concolic Testing for Deep Neural Networks

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车人王/imbalanced-semi-self

[NeurIPS 2020] Semi-Supervision (Unlabeled Data) & Self-Supervision Improve Class-Imbalanced / Long-Tailed Learning

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车人王/MultiRobustness

Code for the paper "Adversarial Training and Robustness for Multiple Perturbations", NeurIPS 2019

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车人王/MetaAttack_ICLR2020