Co-occurring keywords · papers mentioning both
Papers
Generative Modeling through the Semi-dual Formulation of Unbalanced Optimal Transport
NeurIPS 2023
Global-Local Regularization Via Distributional Robustness
AISTATS 2023
Input uncertainty propagation through trained neural networks
ICML 2023
Interpolation for Robust Learning: Data Augmentation on Wasserstein Geodesics
ICML 2023
Large-scale similarity search with Optimal Transport
EMNLP 2023
LAVA: Data Valuation without Pre-Specified Learning Algorithms
ICLR 2023
Learning via Wasserstein-Based High Probability Generalisation Bounds
NeurIPS 2023
Leveraging Label Non-Uniformity for Node Classification in Graph Neural Networks
ICML 2023
Mode-Seeking Divergences: Theory and Applications to GANs
AISTATS 2023
Moments, Random Walks, and Limits for Spectrum Approximation
COLT 2023
Neural approximation of Wasserstein distance via a universal architecture for symmetric and factorwise group invariant functions
NeurIPS 2023
Ollivier-Ricci Curvature for Hypergraphs: A Unified Framework
ICLR 2023
On amortizing convex conjugates for optimal transport
ICLR 2023
On Excess Mass Behavior in Gaussian Mixture Models with Orlicz-Wasserstein Distances
ICML 2023
Optimal Transport Model Distributional Robustness
NeurIPS 2023
Outlier-Robust Wasserstein DRO
NeurIPS 2023
PAC-Bayesian Generalization Bounds for Adversarial Generative Models
ICML 2023
Provable Robustness against Wasserstein Distribution Shifts via Input Randomization
ICLR 2023
Rethinking Initialization of the Sinkhorn Algorithm
AISTATS 2023
Robust Variational Autoencoding with Wasserstein Penalty for Novelty Detection
AISTATS 2023
Sample Complexity of Probability Divergences under Group Symmetry
ICML 2023
Semi-supervised Learning with Support Isolation by Small-Paced Self-Training
AAAI 2023
Statistical Guarantees for Variational Autoencoders using PAC-Bayesian Theory
NeurIPS 2023
Tight Performance Guarantees of Imitator Policies with Continuous Actions
AAAI 2023
Uniform-in-Time Wasserstein Stability Bounds for (Noisy) Stochastic Gradient Descent
NeurIPS 2023