Kediska Shabakadaha Neural Networks ee Sawirka

Jawaabaha iyo sharraxaadaha waxay soo baxayaan markaad qaadanayso kediska.

1. Waa maxay habka xisaabinta xudunta u ah inta badan shabakadaha neural garaafyada?
   • Fariimaha gudbinta iyo isku dhafka u dhexeeya noodhadhka deriska ah
   • Ku dul simbiriirixidda iskuxiran ee shabagga pixel go'an
   • Autoregressive xiga-token saadaasha
   • Socod aan toos ahayn oo aan waxbarasho lahayn
2. Maxay tahay sababta shaqada isu geynta deriska ee GNN ay u noqoto mid aan isbeddelayn?
   • Si aad tababarka uga dhigto mid dhakhso badan
   • Sababtoo ah jaarka garaafku ma laha amar asal ah
   • Sababtoo ah garaafyada mar walba waa la hagayaa
   • Si loo yareeyo tirada halbeegyada hal
3. Waa maxay 'dhaleecaynta xad-dhaafka ah' waxaa loola jeedaa GNN-yada qoto dheer?
   • Sawiradu waxay noqonayaan blur
   • Garaafku wuxuu luminayaa geesihiisa
   • Node-ka-xidhka isku-xidhka ah ee isu imanaya inay noqdaan kuwo isku mid ah marka lakabyadu kordhaan
   • Gradients qarxinaya ilaa xad la'aan
4. How does a Graph Attention Network differ from a basic GCN layer?
   • It removes all graph edges before message passing
   • It assigns each node a unique text token
   • It guarantees deeper networks cannot over-smooth
   • It learns attention coefficients for neighbors, while the GCN uses degree-normalized propagation weights
5. GNN lagu dabaqay molecule, maxay noodhadhka iyo geesaha sida caadiga ah u taagan yihiin?
   • Atomyada iyo curaarta kiimikada
   • Pixels iyo midabada
   • Erayada iyo weedho
   • Isticmaalayaasha iyo boostada
6. Immisa boodbood ayaa akhbaarta u safri karta marinka ka dib lakabyada fariinta gudbinta L?
   • Had iyo jeer dhab ahaan hal rajo
   • Ilaa L hops
   • Garaafyada oo dhan ee hal lakab
   • Eber hops
7. What makes GraphSAGE an inductive graph-learning method?
   • It stores a separate free parameter vector for every possible test node
   • It requires one fixed graph and cannot process new nodes
   • It learns neighborhood aggregation functions that can be applied to unseen nodes
   • It replaces node features with graph-level labels
8. In the original GCN propagation rule, what does symmetric degree normalization do to adjacency messages?
   • Sorts neighboring nodes alphabetically
   • Deletes every edge with a low feature value
   • Makes the graph directed by reversing all edges
   • Scales each edge contribution using the inverse square roots of the source and target node degrees