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LatentConditioning
NameV&UzVh8hUhArchitecture notes
CNP [17]√1√DeepSet encoder,GN node block
AttCNP [27]1√(Attention encoder/decoder
Decoder edge cond. through cross-attention
ConvCNP [28]（√SetConv encoder
NP[18]DeepSet encoder
GraphVAE [20]Graph conv. encoder
VariationalGAE [22]Graph convolutions Iterative decoder
Graphite [21]MP encoder/decoder
NRI [6] MPNP [29]√MP encoder/decoder
DSVNP [16]V²~p(V²|u²,V*，Vh*)
RVAE (this work)一MP encoder/decoder
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MP Steps
Modelmlp unitsNGz sizeenc.dec.agg.# paramsELBO
CRVAE643201mean184,7171.96, (0.30)
643211mean341,5176.99(0.29)
643222mean498,3177.48(0.61)*
643222(comp.)522,8938.11(0.48)*
643233(comp.)679,6937.70(0.53)*
CVAE1286411177,1942.12(0.10)
25664252,5541.17(0.16)
38496111563,1461.23(0.09)
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Caselog p(Vx|Gz; Gh)Range
βε=1.4.16±0.43
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Modelsize (mlp/z/MP Steps)Only cond. on nodes Gh =(Vh,·,·）Cond. on edges and nodes Gh=(Vh,Eh,)
x ∈ [0,1]x∈[1,2]x ∈ [0,1]x∈[1,2]
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NP64/64/NA−1.34(0.07)−11.13(3.08)NANA
128/128/NA−1.08(0.11)-31.74(14.08)NANA
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