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gptkb:Nakagami_distribution
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(2m^m)/(Γ(m)Ω^m) x^{2m-1} exp(-m x^2/Ω), x ≥ 0
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gptkb:Landau_distribution
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no closed-form expression
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gptkb:CityPersons_Dataset
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https://arxiv.org/abs/1702.05693
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gptkb:BERT_on_SQuAD
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gptkb:BERT:_Pre-training_of_Deep_Bidirectional_Transformers_for_Language_Understanding
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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:standard_multivariate_normal_distribution
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(2π)^(-n/2) exp(-1/2 x^T x)
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gptkb:Pearson_Type_VI_distribution
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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:Noncentral_chi-squared_distribution
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Involves modified Bessel function
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gptkb:univariate_t-distribution
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f(x) = Γ((ν+1)/2) / (√(νπ) Γ(ν/2)) (1 + x²/ν)^(-(ν+1)/2)
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gptkb:Standard_Normal_Distribution
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(1/√(2π)) * exp(-x²/2)
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gptkb:YOLOX
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https://arxiv.org/abs/2107.08430
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gptkb:inverse_gamma_distribution
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f(x; α, β) = (β^α / Γ(α)) x^(-α-1) exp(-β/x)
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gptkb:ViT-H
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gptkb:An_Image_is_Worth_16x16_Words:_Transformers_for_Image_Recognition_at_Scale
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gptkb:BERT_on_GLUE
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gptkb:BERT:_Pre-training_of_Deep_Bidirectional_Transformers_for_Language_Understanding
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gptkb:student's_t-distribution
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f(x) = Γ((ν+1)/2) / (√(νπ) Γ(ν/2)) (1 + x²/ν)^(-(ν+1)/2)
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gptkb:Onyx_Boox_Note_Air
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yes
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gptkb:arXiv:1810.09434
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https://arxiv.org/pdf/1810.09434.pdf
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gptkb:DINOv2
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https://arxiv.org/abs/2304.07193
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gptkb:Pearson_Type_0
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f(x) = (1/(σ√(2π))) * exp(- (x-μ)^2 / (2σ^2))
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gptkb:Noncentral_t-distribution
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involves infinite sum
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