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gptkb:Natural_Questions:_A_Benchmark_for_Question_Answering_Research
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https://arxiv.org/abs/1906.00300
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gptkb:Landau_distribution
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no closed-form expression
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gptkb:Standard_Normal_Distribution
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(1/√(2π)) * exp(-x²/2)
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gptkb:chi-squared_distribution
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(1/(2^{k/2}Γ(k/2))) x^{(k/2)-1} e^{-x/2}
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gptkb:Pearson_Type_VII
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f(x) = C [1 + ((x-μ)^2)/(m a^2)]^{-m}
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gptkb:Beta_distribution
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f(x; alpha, beta) = x^{alpha-1} (1-x)^{beta-1} / B(alpha, beta)
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gptkb:Pearson_Type_V
|
f(x; a, b) = (b^a / Γ(a)) x^(-a-1) exp(-b/x)
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gptkb:arXiv:1411.4028
|
https://arxiv.org/pdf/1411.4028.pdf
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gptkb:PageWide_XL_8000
|
yes
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|
gptkb:2004.05150
|
https://arxiv.org/pdf/1706.03762.pdf
|
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gptkb:Pearson_Type_0
|
f(x) = (1/(σ√(2π))) * exp(- (x-μ)^2 / (2σ^2))
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gptkb:Pearson_Type_IX_distribution
|
complex formula involving beta function
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gptkb:Inverse_chi-squared_distribution
|
f(x; ν) = (2^{−ν/2}/Γ(ν/2)) x^{−(ν/2)−1} exp(−1/(2x))
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|
gptkb:arXiv:1810.09434
|
https://arxiv.org/pdf/1810.09434.pdf
|
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gptkb:Normal_distribution_(standard_parameterization)
|
f(x) = (1/(σ√(2π))) * exp(- (x-μ)^2 / (2σ^2))
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gptkb:generalized_Pareto_distribution
|
f(x) = (1/c)(1 + b(x-bc)/c)^{-1/b-1}
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gptkb:Johnson_SB_distribution
|
f(x) = (delta / (lambda * sqrt(2*pi))) * [1 / (y*(1-y))] * exp(-0.5 * [gamma + delta * ln(y/(1-y))]^2), where y = (x - xi)/lambda
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gptkb:Pearson_Type_VI_distribution
|
f(x; α1, α2, β) = (x/β)^{α1-1} / [β B(α1, α2) (1 + x/β)^{α1+α2}] for x > 0
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gptkb:DeepSeek-MoE
|
https://arxiv.org/abs/2405.13237
|
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gptkb:arXiv:1412.6980
|
https://arxiv.org/pdf/1412.6980.pdf
|