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Eric Chan

2 accepted papers

2026

Latent Forcing: Reordering the Diffusion Trajectory for Pixel-Space Image Generation

ICML 2026poster

Latent diffusion models excel at generating high-quality images but lose the benefits of end-to-end modeling. They discard information during image encoding, require a separately trained decoder, and model an auxiliary distribution to the raw data. In this paper, we propose Latent Forcing, a simple …

Cited by 0SourceScholar
2020

MetaSDF: Meta-Learning Signed Distance Functions

NeurIPS 2020poster

Neural implicit shape representations are an emerging paradigm that offers many potential benefits over conventional discrete representations, including memory efficiency at a high spatial resolution. Generalizing across shapes with such neural implicit representations amounts to learning priors ove…