37 Open source projects that are alternatives of or similar to CIL-ReID

Sensor data aggregation tool for any numerical sensor data. Robust and privacy-friendly.

Implementation of the paper "Certifiable Robustness and Robust Training for Graph Convolutional Networks".

Code for AAAI 2018 accepted paper: "Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing their Input Gradients"

阿里云MNS

An Algorithm to Quantify Robustness of Recurrent Neural Networks

Implementation of the WSDM 2021 paper "Node Similarity Preserving Graph Convolutional Networks"

Minimal implementation of Denoised Smoothing (https://arxiv.org/abs/2003.01908) in TensorFlow.

A curated (most recent) list of resources for Learning with Noisy Labels

[NeurIPS 2021]: Are Transformers More Robust Than CNNs? (Pytorch implementation & checkpoints)

(ICML 2022) Official PyTorch implementation of “Blurs Behave Like Ensembles: Spatial Smoothings to Improve Accuracy, Uncertainty, and Robustness”.

Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)

Recentrifuge: robust comparative analysis and contamination removal for metagenomics

contrib/amcheck from Postgres v11 backported to earlier Postgres versions

PyTorch Implementation of Google's Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions. This implementation supports both single-, multi-speaker TTS and several techniques to enforce the robustness and efficiency of the model.

Square Attack: a query-efficient black-box adversarial attack via random search [ECCV 2020]

Generative Forests in Python

NIPS Adversarial Vision Challenge

Adversarial Distributional Training (NeurIPS 2020)

Source code and dataset for the CCKS201 paper "On Robustness and Bias Analysis of BERT-based Relation Extraction"

Robust error-handling for Kotlin and Android

Dynamic Divide-and-Conquer Adversarial Training for Robust Semantic Segmentation （ICCV2021）

RayS: A Ray Searching Method for Hard-label Adversarial Attack (KDD2020)

Code and data for the ICLR 2021 paper "Perceptual Adversarial Robustness: Defense Against Unseen Threat Models".

[CVPR 2022] S-attack library. Official implementation of two papers "Vehicle trajectory prediction works, but not everywhere" and "Are socially-aware trajectory prediction models really socially-aware?".

Figures & code from the paper "Shortcut Learning in Deep Neural Networks" (Nature Machine Intelligence 2020)

Contains code for the paper "Vision Transformers are Robust Learners" (AAAI 2022).

Code and models for ICCV2021 paper "Robust Object Detection via Instance-Level Temporal Cycle Confusion".

A Closer Look at Accuracy vs. Robustness

关于domain generalization，domain adaptation，causality，robutness，prompt，optimization，generative model各式各样研究的阅读笔记

Code used during my Chaos Engineering and Resiliency Patterns talk.

Code for NeurIPS 2019 Paper

Python toolbox to evaluate graph vulnerability and robustness (CIKM 2021)

[NeurIPS'2019] Shupeng Gui, Haotao Wang, Haichuan Yang, Chen Yu, Zhangyang Wang, Ji Liu, “Model Compression with Adversarial Robustness: A Unified Optimization Framework”

Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)

Reachability analysis for closed-loop control systems

PyBullet CartPole and Quadrotor environments—with CasADi symbolic a priori dynamics—for learning-based control and RL

A metric learning method for person re-identification