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  • Forum - OpenReview
    Promoting openness in scientific communication and the peer-review process
  • Flow Matching Policy Gradients - OpenReview
    Flow-based generative models, including diffusion models, excel at modeling continuous distributions in high-dimensional spaces In this work, we introduce Flow Policy Optimization (FPO), a simple on-policy reinforcement learning algorithm that brings flow matching into the policy gradient framework
  • Flow Matching for Denoised Social Recommendation - OpenReview
    This paper introduces RecFlow, a flow-based social recommendation model that captures anisotropic and directed noise in user interactions By leveraging flow matching, RecFlow enhances representation learning and denoising efficiency This work advances understanding of continuous-time generative models in graph-structured data and emphasizes the practical benefits for personalized
  • Time-Gated Multi-Scale Flow Matching for Time-Series Imputation
    We address multivariate time–series imputation by learning the velocity field of a data-conditioned ordinary differential equation (ODE) via flow matching Our method, Time-Gated Multi-Scale Flow Matching (TG-MSFM), conditions the flow on a structured endpoint comprising observed values, a per-time visibility mask, and short left right context, processed by a time-aware Transformer whose
  • F MATCHING FOR GENERATIVE MODELING - OpenReview
    ABSTRACT We introduce a new paradigm for generative modeling built on Continuous Normalizing Flows (CNFs), allowing us to train CNFs at unprecedented scale Specifically, we present the notion of Flow Matching (FM), a simulation-free approach for training CNFs based on regressing vector fields of fixed conditional probability paths Flow Matching is compatible with a general family of Gaussian
  • LapFlow: Laplacian Multi-scale Flow Matching for Generative Modeling
    This paper introduces Laplacian Multi-scale Flow Matching (LapFlow), a novel framework designed to improve the efficiency and scalability of generative modeling To tackle the high computational cost of generating high-resolution images, LapFlow moves away from single-scale generation
  • Forum | OpenReview
    Flow matching and diffusion models are two popular frameworks in generative modeling Despite seeming similar, there is some confusion in the community about their exact connection In this post we
  • F5-TTS: A Fairytaler that Fakes Fluent and Faithful Speech with Flow . . .
    Trained on a public 100K hours multilingual dataset, our Fairytaler Fakes Fluent and Faithful speech with Flow matching (F5-TTS) exhibits highly natural and expressive zero-shot ability, seamless code-switching capability, and speed control efficiency
  • Flower: A Flow-Matching Solver for Inverse Problems
    We introduce Flower, a solver for linear inverse problems It leverages a pre-trained flow model to produce reconstructions that are consistent with the observed measurements Flower operates





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