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20242026
most citedNormalizing Flows are Capable Generative Models

4 citations · 4 across the 9 of their papers we have counts for

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7 papers · 1 filter

cs.CV2026

Normalizing Trajectory Models

Jiatao Gu, Tianrong Chen, Ying Shen +3

Diffusion-based models decompose sampling into many small Gaussian denoising steps -- an assumption that breaks down when generation is compressed to a few coarse transitions. Exis…

cs.CV2026

STARFlow2: Bridging Language Models and Normalizing Flows for Unified Multimodal Generation

Ying Shen, Tianrong Chen, Yuan Gao +6

Deep generative models have advanced rapidly across text and vision, motivating unified multimodal systems that can understand, reason over, and generate interleaved text-image seq…

cs.CV2026

Normalizing Flows with Iterative Denoising

Tianrong Chen, Jiatao Gu, David Berthelot +2

Normalizing Flows (NFs) are a classical family of likelihood-based methods that have received revived attention. Recent efforts such as TARFlow have shown that NFs are capable of a…

cs.CV2025

One Layer Is Enough: Adapting Pretrained Visual Encoders for Image Generation

Yuan Gao, Chen Chen, Tianrong Chen +1

Visual generative models (e.g., diffusion models) typically operate in compressed latent spaces to balance training efficiency and sample quality. In parallel, there has been growi…

cs.CV2025

STARFlow-V: End-to-End Video Generative Modeling with Normalizing Flows

Jiatao Gu, Ying Shen, Tianrong Chen +6

Normalizing flows (NFs) are end-to-end likelihood-based generative models for continuous data, and have recently regained attention with encouraging progress on image generation. Y…

cs.CV2025

STARFlow: Scaling Latent Normalizing Flows for High-resolution Image Synthesis

Jiatao Gu, Tianrong Chen, David Berthelot +7

We present STARFlow, a scalable generative model based on normalizing flows that achieves strong performance in high-resolution image synthesis. The core of STARFlow is Transformer…

cs.CV2024★ 4 cited

Normalizing Flows are Capable Generative Models

Shuangfei Zhai, Ruixiang Zhang, Preetum Nakkiran +7

Normalizing Flows (NFs) are likelihood-based models for continuous inputs. They have demonstrated promising results on both density estimation and generative modeling tasks, but ha…