Search Results for author:
Found 6 papers, 2 papers with code
HexaGen3D: StableDiffusion is just one step away from Fast and Diverse Text-to-3D Generation
Despite the latest remarkable advances in generative modeling, efficient generation of high-quality 3D assets from textual prompts remains a difficult task.
VOLTA: an Environment-Aware Contrastive Cell Representation Learning for Histopathology
To showcase the potential power of our proposed framework, we applied VOLTA to ovarian and endometrial cancers with very small sample sizes (10-20 samples) and demonstrated that our cell representations can be utilized to identify the known histotypes of ovarian cancer and provide novel insights that link histopathology and molecular subtypes of endometrial cancer.
AMIGO: Sparse Multi-Modal Graph Transformer with Shared-Context Processing for Representation Learning of Giga-pixel Images
Processing giga-pixel whole slide histopathology images (WSI) is a computationally expensive task.
CO-PILOT: Dynamic Top-Down Point Cloud with Conditional Neighborhood Aggregation for Multi-Gigapixel Histopathology Image Representation
Importantly, our model is able to stratify the patients into different risk cohorts with statistically different outcomes across two large datasets, a task that was previously achievable only using genomic information.
Sparse Multi-Modal Graph Transformer With Shared-Context Processing for Representation Learning of Giga-Pixel Images
Processing giga-pixel whole slide histopathology images (WSI) is a computationally expensive task.
CCRL: Contrastive Cell Representation Learning
In this work, we investigated the utility of Self-Supervised Learning (SSL) in cell clustering by proposing the Contrastive Cell Representation Learning (CCRL) model.
