Interval attacks (adversarial ML)
☆21Jun 17, 2019Updated 6 years ago
Alternatives and similar repositories for Interval-Attack
Users that are interested in Interval-Attack are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- The library for symbolic interval☆22Jun 23, 2020Updated 5 years ago
- β-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Neural Network Verification☆31Nov 9, 2021Updated 4 years ago
- Analysis of Adversarial Logit Pairing☆60Aug 13, 2018Updated 7 years ago
- Code for FAB-attack☆33Jul 10, 2020Updated 5 years ago
- Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation [NeurIPS 2017]☆18Apr 8, 2018Updated 8 years ago
- GPUs on demand by Runpod - Special Offer Available • AdRun AI, ML, and HPC workloads on powerful cloud GPUs—without limits or wasted spend. Deploy GPUs in under a minute and pay by the second.
- Fourth edition of VNN COMP (2023)☆16Apr 12, 2023Updated 3 years ago
- Benchmarks for the VNN Comp 2023☆16Jun 7, 2024Updated last year
- The official repo for GCP-CROWN paper☆13Sep 26, 2022Updated 3 years ago
- Provable Robustness of ReLU networks via Maximization of Linear Regions [AISTATS 2019]☆31Jul 15, 2020Updated 5 years ago
- ☆15Dec 7, 2021Updated 4 years ago
- Code for paper "Fast and Complete: Enabling Complete Neural Network Verification with Rapid and Massively Parallel Incomplete Verifiers"☆17Jan 27, 2023Updated 3 years ago
- Reference implementations for RecurJac, CROWN, FastLin and FastLip (Neural Network verification and robustness certification algorithms)…☆27Nov 23, 2019Updated 6 years ago
- The released code of Neurify in NIPS 2018☆51Dec 8, 2022Updated 3 years ago
- The released code of ReluVal in USENIX Security 2018☆60Mar 4, 2020Updated 6 years ago
- Serverless GPU API endpoints on Runpod - Bonus Credits • AdSkip the infrastructure headaches. Auto-scaling, pay-as-you-go, no-ops approach lets you focus on innovating your application.
- Comparison of gradient estimation techniques for black-box adversarial examples☆11Oct 31, 2018Updated 7 years ago
- AAAI 2019 oral presentation☆53May 30, 2025Updated 10 months ago
- ☆17Aug 2, 2022Updated 3 years ago
- ☆25Mar 26, 2026Updated 3 weeks ago
- Robustness for Non-Parametric Classification: A Generic Attack and Defense☆18Nov 21, 2022Updated 3 years ago
- [NeurIPS 2020] Code for "An Efficient Adversarial Attack for Tree Ensembles"☆23Jun 6, 2021Updated 4 years ago
- Official implementation for Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds (NeurIPS, 2021).☆25Sep 4, 2022Updated 3 years ago
- Source code for the paper "Exploiting Excessive Invariance caused by Norm-Bounded Adversarial Robustness"☆25Feb 12, 2020Updated 6 years ago
- Overcoming Catastrophic Forgetting by Incremental Moment Matching (IMM)☆35Dec 27, 2017Updated 8 years ago
- Managed Kubernetes at scale on DigitalOcean • AdDigitalOcean Kubernetes includes the control plane, bandwidth allowance, container registry, automatic updates, and more for free.
- A powerful white-box adversarial attack that exploits knowledge about the geometry of neural networks to find minimal adversarial perturb…☆12Aug 5, 2020Updated 5 years ago
- Robust Reinforcement Learning with the Alternating Training of Learned Adversaries (ATLA) framework☆70Jan 26, 2021Updated 5 years ago
- [CVPR'19] Trust Region Based Adversarial Attack☆20Dec 11, 2020Updated 5 years ago
- [ICML'20] Multi Steepest Descent (MSD) for robustness against the union of multiple perturbation models.☆25Jul 25, 2024Updated last year
- A challenge to explore adversarial robustness of neural networks on MNIST.☆761May 3, 2022Updated 3 years ago
- Codes for reproducing the black-box adversarial attacks in “ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural Network…☆63Jun 6, 2019Updated 6 years ago
- Fork of Microsoft/LightGBM to include support for the CEGB (Cost Efficient Gradient Boosting) algorithm. Original repository at https://g…☆13Jun 30, 2017Updated 8 years ago
- A method for training neural networks that are provably robust to adversarial attacks.☆391Feb 16, 2022Updated 4 years ago
- Zeroth-order Min-max Optimization☆13Jun 28, 2020Updated 5 years ago
- Wordpress hosting with auto-scaling - Free Trial • AdFully Managed hosting for WordPress and WooCommerce businesses that need reliable, auto-scalable performance. Cloudways SafeUpdates now available.
- NIPS Adversarial Vision Challenge☆41Sep 17, 2018Updated 7 years ago
- Creating and defending against adversarial examples☆41Jan 6, 2019Updated 7 years ago
- Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)☆99Mar 1, 2022Updated 4 years ago
- Certified defense to adversarial examples using CROWN and IBP. Also includes GPU implementation of CROWN verification algorithm (in PyTor…☆97Jun 7, 2021Updated 4 years ago
- [NeurIPS 2019] H. Chen*, H. Zhang*, S. Si, Y. Li, D. Boning and C.-J. Hsieh, Robustness Verification of Tree-based Models (*equal contrib…☆27Jun 15, 2019Updated 6 years ago
- Code for our NeurIPS 2019 *spotlight* "Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers"☆227Nov 9, 2019Updated 6 years ago
- Code for Stability Training with Noise (STN)☆22Dec 27, 2020Updated 5 years ago