To apply MF to other data modalities, they must also be properly preprocessed into a data matrix with a distribution appropriate to the MF analysis method. When applied to high-throughput omics data, MF techniques learn two matrices: one describes the structure between features (e.g., genes) ...
M ∈ Rn X n is the affinity matrix. Mij represents the similarity between cells i and j if they are mutual neighbors and Mij = 0 otherwise, and n is the number of cells. In other words, the Gaussian kernel transforms the cells from low-dimensional space (dimension = n...
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PyTorch implementation of the Factorized TDNN (TDNN-F) from "Semi-Orthogonal Low-Rank Matrix Factorization for Deep Neural Networks" and Kaldi - cvqluu/Factorized-TDNN
➖ CLIRMatrix: A massively large collection of bilingual and multilingual datasets for Cross-Lingual Information Retrieval. Shuo Sun and Kevin Duh. (paper) (code) ➖ (Findings) Cross-Lingual Training of Neural Models for Document Ranking. Peng Shi, He Bai and Jimmy Lin. (paper) (code) ...
where matrixAand vectorbare uniquely determined from 3D flow vectors at the element vertices. We quantify local nonrigidity in terms of the distance betweenAand the nearest orthogonal matrix (in a mean squared-error sense42,43). In particular, we measure the squared deviation of the singular va...
Although these results must be taken with caution, especially for NNBLI, they still suggest that the predictive power of the two ratios is quite robust to the use of alternative historical vintages. 5. Insights from macro-finance theory The results in the previous sections reveal that the CAPR...
Using this threshold value, we obtain the (l×k) matrix M, with matrix elements Mcp=1 if country c has an RCA for product p, and zero otherwise. This matrix can be viewed as the incidence matrix of a bipartite network linking countries to products. From this matrix, [63] introduced th...
optional arguments: -h, --help show this help message and exit --saved_model_dir_path SAVED_MODEL_DIR_PATH Input saved_model dir path --signature_def SIGNATURE_DEF Specifies the signature name to load from saved_model --input_shapes INPUT_SHAPES Overwrites an undefined input dimension (None...
To leverage inter-individual variability, we learn a matrix\({M}_{s}\in {{\mathbb{R}}}^{{D}_{1},{D}_{1}}\)for each participants ∈ [S] and apply it after the spatial attention layer along the channel dimension. This is similar to but more expressive than the participant ...