6 citations · 6 across the 3 of their papers we have counts for
4 papers
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…
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…
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…
Dyna-AIL : Adversarial Imitation Learning by Planning
Vaibhav Saxena, Srinivasan Sivanandan, Pulkit Mathur
Adversarial methods for imitation learning have been shown to perform well on various control tasks. However, they require a large number of environment interactions for convergenc…