gradient penalty

How to Train Your Latent Control Barrier Function: Smooth Safety Filtering Under Hard-to-Model Constraints L4DC 2026 Neglected Hessian component explains mysteries in sharpness regularization NeurIPS 2024 Euler-Lagrange Analysis of Generative Adversarial Networks JMLR 2023 GradPU: Positive-Unlabeled Learning via Gradient Penalty and Positive Upweighting AAAI 2023 Kantorovich Strikes Back! Wasserstein GANs are not Optimal Transport? NeurIPS 2022 Monotonicity regularization: Improved penalties and novel applications to disentangled representation learning and robust classification UAI 2022 Wasserstein GANs with Gradient Penalty Compute Congested Transport COLT 2022 Bounds all around: training energy-based models with bidirectional bounds NeurIPS 2021 Functional Space Analysis of Local GAN Convergence ICML 2021 Offline Reinforcement Learning with Fisher Divergence Critic Regularization ICML 2021 Adversarial Lipschitz Regularization ICLR 2020 Implicit competitive regularization in GANs ICML 2020 Smoothness and Stability in GANs ICLR 2020 Uncertainty Estimation Using a Single Deep Deterministic Neural Network ICML 2020 Improving Generalization and Stability of Generative Adversarial Networks ICLR 2019 Quality Aware Generative Adversarial Networks NeurIPS 2019 Smooth Deep Image Generator from Noises AAAI 2019 The relativistic discriminator: a key element missing from standard GAN ICLR 2019 Wasserstein of Wasserstein Loss for Learning Generative Models ICML 2019 Banach Wasserstein GAN NeurIPS 2018 Many Paths to Equilibrium: GANs Do Not Need to Decrease a Divergence At Every Step ICLR 2018 Which Training Methods for GANs do actually Converge? ICML 2018 Improved Training of Wasserstein GANs NeurIPS 2017