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Dung Anh Hoang

2 accepted papers

2026

Beyond Uniformity: Sample and Frequency Meta Weighting for Post-Training Quantization of Diffusion Models

ICLR 2026poster

Post-training quantization (PTQ) is an attractive approach for compressing diffusion models to speed up the sampling process and reduce the memory footprint. Most existing PTQ methods uniformly sample data from various time steps in the denoising process to construct a calibration set for quantizati…

Cited by 0SourceScholar
2026

Gradient-Aligned Calibration for Post-Training Quantization of Diffusion Models

ICLR 2026poster

Diffusion models have shown remarkable performance in image synthesis by progressively estimating a smooth transition from a Gaussian distribution of noise to a real image. Unfortunately, their practical deployment is limited by slow inference speed, high memory usage, and the computational demands…

Cited by 0SourceScholar