3 papers
cs.LG2025
Benchmarking and Evaluation of AI Models in Biology: Outcomes and Recommendations from the CZI Virtual Cells Workshop
Elizabeth Fahsbender, Alma Andersson, Jeremy Ash +32
Artificial intelligence holds immense promise for transforming biology, yet a lack of standardized, cross domain, benchmarks undermines our ability to build robust, trustworthy mod…
cs.CV2025
Fast Vision Mamba: Pooling Spatial Dimensions for Accelerated Processing
Saarthak Kapse, Robin Betz, Srinivasan Sivanandan
State Space Models (SSMs) with selective scan (Mamba) have been adapted into efficient vision models. Mamba, unlike Vision Transformers, achieves linear complexity for token intera…
cs.CV2024
Channel Vision Transformers: An Image Is Worth 1 x 16 x 16 Words
Yujia Bao, Srinivasan Sivanandan, Theofanis Karaletsos
Vision Transformer (ViT) has emerged as a powerful architecture in the realm of modern computer vision. However, its application in certain imaging fields, such as microscopy and s…