Decoding BINNs: Bridging Data and Biology
Biologically-informed neural networks (BINNs) promise insights into complex biological processes. Our exploration reveals that success hinges on balancing architecture and data.
Read the full articleYou might also wanna read
Inferring stochastic dynamics by biophysical Neural ODE using single-cell transcriptomics
Discovering cell fate dynamics redefined! DynNet integrates Neural ODEs for superior single-cell RNA insights, balancing mechanistic realism

ProteinNetworkSight: A web platform for analyzing multi-feature biological data through interactive network visualization
Abstract. ProteinNetworkSight ( addresses a pervasive bottleneck in modern systems biology: the inability to simultaneou
Wider Neural Networks with Fewer Parameters Improve Performance by Reducing Feature Interference
This work demonstrates how increasing the number of neurons in a network without increasing its total number of non-zero parameters improves
Network architecture follows coupling in multiphysics systems: single vs. multiple branches in DeepONet and S-DeepONet
Network architecture follows coupling in multiphysics systems: single vs. multiple branches in DeepONet and S-DeepONet
Researchers Work to Decode the "Black Box" of Reservoir Computing and Brain-Inspired AI
Deciphering the Secrets Within Artificial Neurons
Dragon Hatchling: A Biologically-Inspired LLM Architecture Bridging Transformers and Brain Models
The relationship between computing systems and the brain has served as motivation for pioneering theoreticians since John von Neumann and Al

Comments
Sign in to join the conversation.
No comments yet. Be the first.