7 papers · ranked by Valyu relevance
Charles de Kergariou, Helmut Hauser, David Correa
Advances in novel materials science enable structures to function as intelligent machines by embedding memory and learning capabilities directly into materials. Our work introduces a physical adaptive material motor unit neural network, leveraging a new generation of controllable actuators composed of wood- and carbon…
Yi Ren, Zimei Chen, Hayden Deans, Ying Nian Wu + 1 more
Extensive studies suggest the brain performs Bayesian inference to infer the latent world states. It is a fundamental neuroscience question that how canonical recurrent neural circuits in the brain implement Bayesian inference. Many existing theoretical studies focused on how the recurrent circuits compute the…
Eliezer Masliah
How transient neural representations become integrated and stable enough to function as internal neural models remains incompletely understood. Grounded in efficient coding, Bayesian and predictive frameworks, recurrent and attractor dynamics, neural state-space models, and systems neuroscience, the Principle of…
Maryam Majeed, Mara C.P. Rue, Aixin Zhang, Sabrina Cheng + 14 more
Parallel visual streams segregate information into pathways specialized for distinct computations, but how this segregation is achieved by anatomical segregation of primary visual cortex output remains unclear. This problem is complicated because individual neurons frequently send broadcasting projections to multiple…
Xiaoyue Hu, Yuhao Ma, Ruixing Ming, Heping Zhang + 1 more
Identifying essential biomarkers remains a core challenge in elucidating the pathogenic mechanisms and achieving precise diagnosis of complex diseases. Deep neural networks offer immense predictive power, yet their lack of interpretability severely limits downstream biological insight. Here, we introduce DeepVaris, an…
Hadeer Kamal, Amira Y. Haikal, Mahmoud M. Saafan
Traffic collisions and congestion represent significant challenges within intelligent transportation systems (ITS). Consequently, a vehicular ad-hoc network (VANET) has been established. Numerous architectures have been incorporated into VANETs to manage the extensive data generated by vehicles. Collaboration with fog…
Matteo Farina, Pietro Zamberlan, Arno Onken, Ulisse Ferrari
For datasets with thousands of neurons and images, vision transformers have proven successful at predicting neural responses to stimuli. However, they are expected to underperform in low-data regimes, where CNNs and Gaussian processes are considered more effective. We ask whether transformers can be made competitive…