Co-occurring keywords · papers mentioning both
Papers
Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation
UAI 2026
Accelerating optimization over the space of probability measures
JMLR 2025
Expected Sliced Transport Plans
ICLR 2025
Geodesic Slice Sampling on the Sphere
JMLR 2025
Linearized Wasserstein Barycenters: Synthesis, Analysis, Representational Capacity, and Applications
AISTATS 2025
The Relativity of Causal Knowledge
UAI 2025
A Specialized Semismooth Newton Method for Kernel-Based Optimal Transport
AISTATS 2024
Characterization of translation invariant MMD on Rd and connections with Wasserstein distances
JMLR 2024
Functional Flow Matching
AISTATS 2024
LCOT: Linear Circular Optimal Transport
ICLR 2024
Minimizing Convex Functionals over Space of Probability Measures via KL Divergence Gradient Flow
AISTATS 2024
Neural Optimal Transport with Lagrangian Costs
UAI 2024
Non-geodesically-convex optimization in the Wasserstein space
NeurIPS 2024
Tangential Wasserstein Projections
JMLR 2024
The Star Geometry of Critic-Based Regularizer Learning
NeurIPS 2024
An Homogeneous Unbalanced Regularized Optimal Transport Model with Applications to Optimal Transport with Boundary
AISTATS 2023
Efficient displacement convex optimization with particle gradient descent
ICML 2023
Fast Optimal Transport through Sliced Generalized Wasserstein Geodesics
NeurIPS 2023
Gaussian Processes on Distributions based on Regularized Optimal Transport
AISTATS 2023
Hierarchical Sliced Wasserstein Distance
ICLR 2023
Learning Rate Free Sampling in Constrained Domains
NeurIPS 2023
Learning with Stochastic Orders
ICLR 2023
Metrizing Weak Convergence with Maximum Mean Discrepancies
JMLR 2023
Riemannian Metric Learning via Optimal Transport
ICLR 2023
Volumetric Optimal Transportation by Fast Fourier Transform
ICLR 2023