4 papers
Incorporating contextual information into KGWAS for interpretable GWAS discovery
Cheng Jiang, Brady Ryan, Megan Crow +7
Genome-Wide Association Studies (GWAS) identify associations between genetic variants and disease; however, moving beyond associations to causal mechanisms is critical for therapeu…
Group Contrastive Learning for Weakly Paired Multimodal Data
Aditya Gorla, Hugues Van Assel, Jan-Christian Huetter +4
We present GROOVE, a semi-supervised multi-modal representation learning approach for high-content perturbation data where samples across modalities are weakly paired through share…
Sparse Mixture-of-Experts for Multi-Channel Imaging: Are All Channel Interactions Required?
Sukwon Yun, Heming Yao, Burkhard Hoeckendorf +3
Vision Transformers () have become the backbone of vision foundation models, yet their optimization for multi-channel domains - such as cell painting or satellite imag…
Supervised Contrastive Block Disentanglement
Taro Makino, Ji Won Park, Natasa Tagasovska +11
Real-world datasets often combine data collected under different experimental conditions. This yields larger datasets, but also introduces spurious correlations that make it diffic…