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Found 9 papers, 4 papers with code
Physics-based machine learning for modeling stochastic IP3-dependent calcium dynamics
We present a machine learning method for model reduction which incorporates domain-specific physics through candidate functions.
Learning Dynamic Boltzmann Distributions as Reduced Models of Spatial Chemical Kinetics
Finding reduced models of spatially-distributed chemical reaction networks requires an estimation of which effective dynamics are relevant.
Biological Physics Statistical Mechanics
Deep Learning Moment Closure Approximations using Dynamic Boltzmann Distributions
Moment closure methods are used to approximate a subset of low order moments by terminating the hierarchy at some order and replacing higher order terms with functions of lower order ones.
Internal Feedback in Biological Control: Architectures and Examples
In biology, in addition to typical feedback between plant and controller, we observe feedback pathways within control systems, which we call internal feedback pathways (IFPs), that are often very complex.
Large Language Models and the Reverse Turing Test
If so, then by studying interviews we may be learning more about the intelligence and beliefs of the interviewer than the intelligence of the LLMs.
Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution
Neuroscience has long been an essential driver of progress in artificial intelligence (AI).
Temporally Layered Architecture for Adaptive, Distributed and Continuous Control
Our design is biologically inspired and draws on the architecture of the human brain which executes actions at different timescales depending on the environment's demands.
Temporally Layered Architecture for Efficient Continuous Control
We present a temporally layered architecture (TLA) for temporally adaptive control with minimal energy expenditure.
Traveling Waves Encode the Recent Past and Enhance Sequence Learning
Traveling waves of neural activity have been observed throughout the brain at a diversity of regions and scales; however, their precise computational role is still debated.
