Summary of Maximizing the Potential Of Synthetic Data: Insights From Random Matrix Theory, by Aymane El Firdoussi et al.
Maximizing the Potential of Synthetic Data: Insights from Random Matrix Theoryby Aymane El Firdoussi, Mohamed…
Summary of Score Neural Operator: a Generative Model For Learning and Generalizing Across Multiple Probability Distributions, by Xinyu Liao et al.
Score Neural Operator: A Generative Model for Learning and Generalizing Across Multiple Probability Distributionsby Xinyu…
Summary of The Plug-in Approach For Average-reward and Discounted Mdps: Optimal Sample Complexity Analysis, by Matthew Zurek et al.
The Plug-in Approach for Average-Reward and Discounted MDPs: Optimal Sample Complexity Analysisby Matthew Zurek, Yudong…
Summary of Eventflow: Forecasting Continuous-time Event Data with Flow Matching, by Gavin Kerrigan et al.
EventFlow: Forecasting Continuous-Time Event Data with Flow Matchingby Gavin Kerrigan, Kai Nelson, Padhraic SmythFirst submitted…
Summary of Diversity-rewarded Cfg Distillation, by Geoffrey Cideron et al.
Diversity-Rewarded CFG Distillationby Geoffrey Cideron, Andrea Agostinelli, Johan Ferret, Sertan Girgin, Romuald Elie, Olivier Bachem,…
Summary of Defog: Discrete Flow Matching For Graph Generation, by Yiming Qin et al.
DeFoG: Discrete Flow Matching for Graph Generationby Yiming Qin, Manuel Madeira, Dorina Thanou, Pascal FrossardFirst…
Summary of Efficient Training Of Neural Stochastic Differential Equations by Matching Finite Dimensional Distributions, By Jianxin Zhang et al.
Efficient Training of Neural Stochastic Differential Equations by Matching Finite Dimensional Distributionsby Jianxin Zhang, Josh…
Summary of Posterior Sampling Via Langevin Dynamics Based on Generative Priors, by Vishal Purohit et al.
Posterior sampling via Langevin dynamics based on generative priorsby Vishal Purohit, Matthew Repasky, Jianfeng Lu,…
Summary of Discrete Copula Diffusion, by Anji Liu et al.
Discrete Copula Diffusionby Anji Liu, Oliver Broadrick, Mathias Niepert, Guy Van den BroeckFirst submitted to…
Summary of Bellman Diffusion: Generative Modeling As Learning a Linear Operator in the Distribution Space, by Yangming Li et al.
Bellman Diffusion: Generative Modeling as Learning a Linear Operator in the Distribution Spaceby Yangming Li,…