Alternatives and similar repositories for trickster

Users that are interested in trickster are comparing it to the libraries listed below

• bogdan-kulynych / textfool
  Plausible looking adversarial examples for text classification
  ☆94Updated 7 years ago
• Eric-Wallace / data-poisoning
  Concealed Data Poisoning Attacks on NLP Models
  ☆21Updated 2 years ago
• neulab / RIPPLe
  Code for the paper "Weight Poisoning Attacks on Pre-trained Models" (ACL 2020)
  ☆143Updated 4 months ago
• max-andr / provably-robust-boosting
  Provably Robust Boosted Decision Stumps and Trees against Adversarial Attacks [NeurIPS 2019]
  ☆50Updated 5 years ago
• QData / deepWordBug
  CodeBase for Paper: "Black-box Generation of Adversarial Text Sequences to Evade Deep Learning Classifiers", / Interactive Demo @
  ☆80Updated 2 years ago
• robust-ml / robust-ml.github.io
  A community-run reference for state-of-the-art adversarial example defenses.
  ☆51Updated last year
• kohpangwei / data-poisoning-release
  ☆33Updated 8 years ago
• facebookresearch / private_prediction
  The code reproduces the results of the experiments in the paper. In particular, it performs experiments in which machine-learning models …
  ☆20Updated 4 years ago
• Eric-Wallace / adversarial-mt
  Code for "Imitation Attacks and Defenses for Black-box Machine Translations Systems"
  ☆35Updated 5 years ago
• vikramnitin9 / adversarial-learning-literature
  ☆37Updated 5 years ago
• ddkang / advex-uar
  Code for "Testing Robustness Against Unforeseen Adversaries"
  ☆80Updated last year
• nesl / nlp_adversarial_examples
  Implementation code for the paper "Generating Natural Language Adversarial Examples"
  ☆170Updated 6 years ago
• google-research / selfstudy-adversarial-robustness
  ☆130Updated 4 years ago
• google / TrustScore
  To Trust Or Not To Trust A Classifier. A measure of uncertainty for any trained (possibly black-box) classifier which is more effective t…
  ☆178Updated 2 years ago
• peterbhase / InterpretableNLP-ACL2020
  Code for "Evaluating Explainable AI: Which Algorithmic Explanations Help Users Predict Model Behavior?"
  ☆45Updated 2 years ago
• eth-sri / diffai
  A certifiable defense against adversarial examples by training neural networks to be provably robust
  ☆222Updated last year
• robust-ml / robustml
  Interfaces for defining Robust ML models and precisely specifying the threat models under which they claim to be secure.
  ☆62Updated 6 years ago
• uclanlp / reducingbias
  ☆84Updated 4 years ago
• QData / AdversarialDNN-Playground
  VizSec17: Web-based visualization tool for adversarial machine learning / LiveDemo
  ☆130Updated 2 years ago
• evaluating-adversarial-robustness / adv-eval-paper
  LaTeX source for the paper "On Evaluating Adversarial Robustness"
  ☆259Updated 4 years ago
• Lab41 / cyphercat
  Implementation of membership inference and model inversion attacks, extracting training data information from an ML model. Benchmarking …
  ☆103Updated 6 years ago
• csong27 / collision-bert
  ☆25Updated 5 years ago
• IBM / Contrastive-Explanation-Method
  Codes for reproducing the contrastive explanation in “Explanations based on the Missing: Towards Contrastive Explanations with Pertinent…
  ☆54Updated 7 years ago
• Hadisalman / smoothing-adversarial
  Code for our NeurIPS 2019 *spotlight* "Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers"
  ☆228Updated 6 years ago
• cecilialeiqi / adversarial_text
  to add
  ☆20Updated 6 years ago
• csinva / hierarchical-dnn-interpretations
  Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)
  ☆129Updated 4 years ago
• max-andr / provable-robustness-max-linear-regions
  Provable Robustness of ReLU networks via Maximization of Linear Regions [AISTATS 2019]
  ☆31Updated 5 years ago
• equialgo / fairness-in-ml
  This repository contains the full code for the "Towards fairness in machine learning with adversarial networks" blog post.
  ☆119Updated 4 years ago
• nikikilbertus / blind-justice
  Blind Justice Code for the paper "Blind Justice: Fairness with Encrypted Sensitive Attributes", ICML 2018
  ☆14Updated 6 years ago
• yanaiela / demog-text-removal
  ☆51Updated 7 years ago