Sökning: "neural connectivity"
Visar resultat 1 - 5 av 45 uppsatser innehållade orden neural connectivity.
1. On Linear Mode Connectivity up to Permutation of Hidden Neurons in Neural Network : When does Weight Averaging work?
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Neural networks trained using gradient-based optimization methods exhibit a surprising phenomenon known as mode connectivity, where two independently trained network weights are not isolated low loss minima in the parameter space. Instead, they can be connected by simple curves along which the loss remains low. LÄS MER
2. Regression with Bayesian Confidence Propagating Neural Networks
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Bayesian Confidence Propagating Neural Networks (BCPNNs) are biologically inspired artificial neural networks. These networks have been modeled to account for brain-like aspects such as modular architecture, divisive normalization, sparse connectivity, and Hebbian learning. LÄS MER
3. Neural functional connections of pragmatics : A potential pragmatic network in development
Magister-uppsats, Stockholms universitet/Institutionen för lingvistikSammanfattning : Pragmatic ability is crucial in everyday interactions. In populations of neurotypical individuals, pragmatic skill varies greatly. The neural mechanisms behind the variety, and the neural development of pragmatics remain to be explained. LÄS MER
4. The data-driven CyberSpine : Modeling the Epidural Electrical Stimulation using Finite Element Model and Artificial Neural Networks
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Every year, 250,000 people worldwide suffer a spinal cord injury (SCI) that leaves them with chronic paraplegia - permanent loss of ability to move their legs. SCI interrupts axons passing along the spinal cord, thereby isolating motor neurons from brain inputs. To date, there are no effective treatments that can reconnect these interrupted axons. LÄS MER
5. Link Prediction Using Learnable Topology Augmentation
Master-uppsats, KTH/Matematik (Avd.)Sammanfattning : Link prediction is a crucial task in many downstream applications of graph machine learning. Graph Neural Networks (GNNs) are a prominent approach for transductive link prediction, where the aim is to predict missing links or connections only within the existing nodes of a given graph. LÄS MER