Research map / Adversarial robustness and security / Attacks on text and graphs
Don't let your Discriminator be fooled
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Closest papers by meaning
- Generative Modeling Using the Sliced Wasserstein Distance (CVPR 2018 · similarity 0.92)
- Hidden Convexity of Wasserstein GANs: Interpretable Generative Models with Closed-Form Solutions (ICLR 2022 · similarity 0.92)
- Wasserstein Adversarial Examples via Projected Sinkhorn Iterations (ICML 2019 · similarity 0.91)
- On the Convergence and Robustness of Training GANs with Regularized Optimal Transport (NeurIPS 2018 · similarity 0.91)
- A Two-Step Computation of the Exact GAN Wasserstein Distance (ICML 2018 · similarity 0.91)
- Approximability of Discriminators Implies Diversity in GANs (ICLR 2019 · similarity 0.90)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.