7 citations · 7 across the 4 of their papers we have counts for
4 papers
EchoJEPA: A Latent Predictive Foundation Model for Echocardiography
Alif Munim, Adibvafa Fallahpour, Teodora Szasz +9
Foundation models for echocardiography often struggle to disentangle anatomical signal from the stochastic speckle and acquisition artifacts inherent to ultrasound. We present Echo…
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…
Splicing Up Your Predictions with RNA Contrastive Learning
Philip Fradkin, Ruian Shi, Bo Wang +2
In the face of rapidly accumulating genomic data, our understanding of the RNA regulatory code remains incomplete. Recent self-supervised methods in other domains have demonstrated…
NodeCoder: a graph-based machine learning platform to predict active sites of modeled protein structures
Nasim Abdollahi, Seyed Ali Madani Tonekaboni, Jay Huang +2
While accurate protein structure predictions are now available for nearly every observed protein sequence, predicted structures lack much of the functional context offered by exper…