Native R and Python sample-deletion robustness for omics: candidate certificates, minimum deletion bounds, Bioconductor model refits and donor-level pseudobulk
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Updated
Oct 7, 2026 - HTML
Native R and Python sample-deletion robustness for omics: candidate certificates, minimum deletion bounds, Bioconductor model refits and donor-level pseudobulk
[TPAMI 2023 / ACMMM 2022 Best Paper Runner-Up Award] Learnability Enhancement for Low-light Raw Denoising: Where Paired Real Data Meets Noise Modeling (a Data Perspective)
Learning image-to-image translation using paired and unpaired training samples
Curated Turkish prompt-injection dataset by Enes Deniz, with paired benign and attack examples for LLM security and AI red/blue teaming.
This project implements a CycleGAN-based method for image dehazing on a paired dataset containing hazy images and their corresponding ground truth clear images.
A reproducible R workflow for paired count data, repeated experimental units, beta-binomial and negative-binomial models, and synthetic-data validation.
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