xLeaF Lab
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- awesome-alignment-of-diffusion-models Public
The collection of awesome papers on alignment of diffusion models.
xie-lab-ml/awesome-alignment-of-diffusion-models’s past year of commit activity - Golden-Noise-for-Diffusion-Models Public
[ICCV2025] The code of our work "Golden Noise for Diffusion Models: A Learning Framework".
xie-lab-ml/Golden-Noise-for-Diffusion-Models’s past year of commit activity - multiphysics-bench Public
We propose the first Multiphysics Bench for benchmarking and investigating Scientific Machine Learning for solving multiphysics PDEs.
xie-lab-ml/multiphysics-bench’s past year of commit activity - flow-inference-enhancement Public
We propose a novel training-free inference enhancement method for flow-based diffusion models.
xie-lab-ml/flow-inference-enhancement’s past year of commit activity - Weak-to-Strong-Diffusion-with-Reflection Public
The official code of "Weak-to-Strong Diffusion with Reflection".
xie-lab-ml/Weak-to-Strong-Diffusion-with-Reflection’s past year of commit activity - CoRe2 Public
The official implementation of our paper "CoRe^2: Collect, Reflect and Refine to Generate Better and Faster".
xie-lab-ml/CoRe2’s past year of commit activity - Zigzag-Diffusion-Sampling Public
[ICLR2025] The code of Z-Sampling, proposed in our paper "Zigzag Diffusion Sampling: Diffusion Models Can Self-Improve via Self-Reflection".
xie-lab-ml/Zigzag-Diffusion-Sampling’s past year of commit activity - IV-mixed-Sampler Public
[ICLR2025] IV-Mixed Sampler: Leveraging Image Diffusion Models for Enhanced Video Synthesis
xie-lab-ml/IV-mixed-Sampler’s past year of commit activity - Meissonic-Inference Public
Bag of Design Choices for Inference of High-Resolution Masked Generative Transformer
xie-lab-ml/Meissonic-Inference’s past year of commit activity - deep-learning-dynamics-paper-list Public
This is a list of peer-reviewed representative papers on deep learning dynamics (optimization dynamics of neural networks). The success of deep learning attributes to both network architecture and stochastic optimization. Thus, deep learning dynamics play an essentially important role in theoretical foundation of deep learning.
xie-lab-ml/deep-learning-dynamics-paper-list’s past year of commit activity
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