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Search results for python robustness

131 search results found

Promptbench ⭐ 1,655

A unified evaluation framework for large language models

Robustness ⭐ 728

Corruption and Perturbation Robustness (ICLR 2019)

Openood ⭐ 681

Benchmarking Generalized Out-of-Distribution Detection

Natural Adv Examples ⭐ 559

A Harder ImageNet Test Set (CVPR 2021)

Safe Control Gym ⭐ 477

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

Faceimagequality ⭐ 416

Code and information for face image quality assessment with SER-FIQ

Awesome Out Of Distribution Detection ⭐ 400

A professionally curated list of papers, tutorials, books, videos, articles and open-source libraries etc for Out-of-distribution detection, robustness, and generalization

Assembled Cnn ⭐ 311

Tensorflow implementation of "Compounding the Performance Improvements of Assembled Techniques in a Convolutional Neural Network"

Model Vs Human ⭐ 301

Benchmark your model on out-of-distribution datasets with carefully collected human comparison data (NeurIPS 2021 Oral)

Diffusion Classifier ⭐ 255

Diffusion Classifier leverages pretrained diffusion models to perform zero-shot classification without additional training

Extend python lists operations using .NET's LINQ syntax for clean and fast coding.

Auto_lirpa ⭐ 239

auto_LiRPA: An Automatic Linear Relaxation based Perturbation Analysis Library for Neural Networks and General Computational Graphs

Robodepth ⭐ 229

[NeurIPS'23] RoboDepth: Robust Out-of-Distribution Depth Estimation under Corruptions

Is Chatgpt A Good Translator ⭐ 209

A preliminary evaluation of ChatGPT/GPT-4 for machine translation.

Self-Supervised Learning for OOD Detection (NeurIPS 2019)

Modelnet40 C ⭐ 184

Repo for "Benchmarking Robustness of 3D Point Cloud Recognition against Common Corruptions" https://arxiv.org/abs/2201.12296

Pointcloud C ⭐ 159

Benchmarking and Analyzing Point Cloud Perception Robustness under Corruptions

Fiddler Auditor ⭐ 108

Fiddler Auditor is a tool to evaluate language models.

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

ST-SSL (STSSL): Spatio-Temporal Self-Supervised Learning for Traffic Flow Forecasting/Prediction

Imagenet R ⭐ 103

ImageNet-R(endition) and DeepAugment (ICCV 2021)

Test Time Adaptation ⭐ 103

A repository and benchmark for online test-time adaptation.

Evaluation Of Chatgpt On Information Extraction ⭐ 100

An Evaluation of ChatGPT on Information Extraction task, including Named Entity Recognition (NER), Relation Extraction (RE), Event Extraction (EE) and Aspect-based Sentiment Analysis (ABSA).

Free_adv_train ⭐ 95

Official TensorFlow Implementation of Adversarial Training for Free! which trains robust models at no extra cost compared to natural training.

S Attack ⭐ 85

[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?".

Recentrifuge ⭐ 83

Recentrifuge: robust comparative analysis and contamination removal for metagenomics

Vits Vs Cnns ⭐ 79

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

Pre Training ⭐ 79

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

[AAAI22 Oral] Reliable Propagation-Correction Modulation for Video Object Segmentation

[CVPR 2020] When NAS Meets Robustness: In Search of Robust Architectures against Adversarial Attacks

Cycle Confusion ⭐ 73

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

Cil Reid ⭐ 68

Benchmarks for Corruption Invariant Person Re-identification. [NeurIPS 2021 Track on Datasets and Benchmarks]

Augmix_tf2 ⭐ 67

TF2.0 port for Augmix paper

Shortcut Perspective ⭐ 67

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

Understanding Fast Adv Training ⭐ 67

Understanding and Improving Fast Adversarial Training [NeurIPS 2020]

Crown Ibp ⭐ 64

Certified defense to adversarial examples using CROWN and IBP. Also includes GPU implementation of CROWN verification algorithm (in PyTorch).

Face Robustness Benchmark ⭐ 63

An adversarial robustness evaluation library on face recognition.

Beyond Inet ⭐ 62

Code for experiments for "ConvNet vs Transformer, Supervised vs CLIP: Beyond ImageNet Accuracy"

This is an official PyTorch implementation of the ICML 2023 paper AdaNPC and SIGKDD paper DRM.

Modelnet C ⭐ 52

[ICML 2022] Benchmarking and Analyzing Point Cloud Classification under Corruptions https://arxiv.org/abs/2202.03377

[ICCV 2021] Amplitude-Phase Recombination: Rethinking Robustness of Convolutional Neural Networks in Frequency Domain

Spatial Smoothing ⭐ 51

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

Robust Local Lipschitz ⭐ 50

A Closer Look at Accuracy vs. Robustness

[CVPR 2022 Oral] Official PyTorch implementation of FIFO

Onlinelabelsmoothing ⭐ 45

The official code for the paper "Delving Deep into Label Smoothing", IEEE TIP 2021

Robust Video Object Segmentation ⭐ 41

[ACM MM22] Towards Robust Video Object Segmentation with Adaptive Object Calibration, ACM Multimedia 2022

Perceptual Advex ⭐ 39

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

Simple, compact, and hackable post-hoc deep OOD detection for already trained tensorflow or pytorch image classifiers.

Adversarial Vision Challenge ⭐ 36

NIPS Adversarial Vision Challenge

Informative Outlier Mining ⭐ 35

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.

[ICML 2019] ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation

Causalmotion ⭐ 33

[CVPR22] Towards Robust and Adaptive Motion Forecasting: A Causal Representation Perspective

Code for paper: SDE-Net: Equipping Deep Neural network with Uncertainty Estimates

A implementation of Power Normalized Cepstral Coefficients: PNCC

Mdl Stance Robustness ⭐ 31

Multi-dataset stance detection and robustness experiments

Revisiting At ⭐ 31

Code for the paper "Revisiting Adversarial Training for ImageNet: Architectures, Training and Generalization across Threat Models"

Adversarial Distributional Training ⭐ 31

Adversarial Distributional Training (NeurIPS 2020)

[ICCV'19] Improving Adversarial Robustness via Guided Complement Entropy

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

Learnable Boundary Guided Adversarial Training (ICCV2021)

[ICLR 2022] Understanding and Improving Graph Injection Attack by Promoting Unnoticeability

An Algorithm to Quantify Robustness of Recurrent Neural Networks

Romtrack ⭐ 28

[ICCV 2023] Robust Object Modeling for Visual Tracking, Official Implementation

Square Attack ⭐ 27

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

Raw2logit ⭐ 27

In order to control processing-induced dataset drift we require two ingredients: raw sensor data and an image processing model. This code repository contains the materials for the second ingredient, the image processing models, as well as scripts to load data and run experiments. https://arxiv.org/abs/2211.02578

Releasing code for "ReCode: Robustness Evaluation of Code Generation Models"

[ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"

Online_test_time_adaptation ⭐ 25

Revisiting Test Time Adaptation Under Online Evaluation

Fourierheatmap ⭐ 24

Unofficial pytorch implementation of Fourier Heat Map proposed in 'A Fourier Perspective on Model Robustness in Computer Vision' [Yin+, NeurIPS2019]

Neural Ode Metasolver ⭐ 24

Supplementary code for the paper "Meta-Solver for Neural Ordinary Differential Equations" https://arxiv.org/abs/2103.08561

Muad Dataset ⭐ 23

MUAD: Multiple Uncertainties for Autonomous Driving, a benchmark for multiple uncertainty types and tasks [BMVC 2022]

Comprehensive Tacotron2 ⭐ 23

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.

Adversarial_mter ⭐ 23

Code for ICCV2019 paper《Adversarial Learning with Margin-based Triplet Embedding Regularization》

Triple Wins ⭐ 22

[ICLR 2020] ”Triple Wins: Boosting Accuracy, Robustness and Efficiency Together by Enabling Input-Adaptive Inference“

[MICCAI 2022 Best Paper Finalist] Bayesian Pseudo Labels: Expectation Maximization for Robust and Efficient Semi Supervised Segmentation

Diagnosere ⭐ 21

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

Viewfool_ ⭐ 20

This repository contains the ViewFool and ImageNet-V proposed by the paper “ViewFool: Evaluating the Robustness of Visual Recognition to Adversarial Viewpoints” (NeurIPS2022).

Splitmix ⭐ 20

[ICLR2022] Efficient Split-Mix federated learning for in-situ model customization during both training and testing time

Deel Torchlip ⭐ 20

Build and train Lipschitz-constrained networks: PyTorch implementation of 1-Lipschitz layers

Rationale Robustness ⭐ 19

NAACL 2022: Can Rationalization Improve Robustness? https://arxiv.org/abs/2204.11790

Smoothing Consistency ⭐ 19

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

Robustarchitecturesearch ⭐ 18

This github repository contains the official code for the paper, "Evolving Robust Neural Architectures to Defend from Adversarial Attacks"

Metric_learning_adversarial_robustness ⭐ 17

Code for NeurIPS 2019 Paper

Robust Semantic Segmentation ⭐ 17

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

Adversarial Nonparametrics ⭐ 17

Robustness for Non-Parametric Classification: A Generic Attack and Defense

Gpt 4v Distribution Shift ⭐ 16

Code for "How Well Does GPT-4V(ision) Adapt to Distribution Shifts? A Preliminary Investigation"

Vllm Safety Benchmark ⭐ 15

Official PyTorch Implementation of "How Many Unicorns Are in This Image? A Safety Evaluation Benchmark for Vision LLMs"

Specification_curve ⭐ 15

Specification Curve is a Python package that performs specification curve analysis: exploring how a coefficient varies under multiple different specifications of a statistical model.

Robust Nets ⭐ 14

Official implementation of the paper "Solving Inverse Problems With Deep Neural Networks - Robustness Included?" by M. Genzel, J. Macdonald, and M. März (2020).

Code used during my Chaos Engineering and Resiliency Patterns talk.

Ttt Plus Plus ⭐ 14

[NeurIPS21] TTT++: When Does Self-supervised Test-time Training Fail or Thrive?

Nat Acl2020 ⭐ 13

Official code for `Visual Attention Emerges from Recurrent Sparse Reconstruction' (ICML 2022)

Simp Gcn ⭐ 12

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

Aileen Core ⭐ 12

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

Robust Principles ⭐ 12

Robust Principles: Architectural Design Principles for Adversarially Robust CNNs

Mercury Robust ⭐ 12

mercury-robust is a framework to perform robust testing on ML models and datasets. It provides a collection of test that are easy to configure and helpful to guarantee robustness in your ML processes.

Contrastive Poisoning ⭐ 12

[ICLR 2023, Spotlight] Indiscriminate Poisoning Attacks on Unsupervised Contrastive Learning

Dynamic_adv_training ⭐ 11

Code for ICML2019 Paper "On the Convergence and Robustness of Adversarial Training"

Low Shot Robustness ⭐ 11

Code for the ICCV 2023 paper "Benchmarking Low-Shot Robustness to Natural Distribution Shifts"

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