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Tensor Decomposition

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/AutoML-Research/S2S

공식 코드

Searching to Sparsify Tensor Decomposition for N-ary Relational Data

https://github.com/BethanyL/SCTD

공식 코드

Shape Constrained Tensor Decompositions using Sparse Representations in Over-Complete Libraries

https://github.com/BioMedicalBigDataMiningLab/TDRC

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Tensor Decomposition with Relational Constraints for Predicting Multiple Types of MicroRNA-disease Associations

https://github.com/Cadene/block.bootstrap.pytorch

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BLOCK: Bilinear Superdiagonal Fusion for Visual Question Answering and Visual Relationship Detection

https://github.com/Ebiquity/KGFP

공식 코드

Knowledge Graph Fact Prediction via Knowledge-Enriched Tensor Factorization

https://github.com/FurongHuang/Fast-Detection-of-Overlapping-Communities-via-Online-Tensor-Methods

공식 코드

Online Tensor Methods for Learning Latent Variable Models

https://github.com/HELL-TO-HEAVEN/KGE-CL

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KGE-CL: Contrastive Learning of Tensor Decomposition Based Knowledge Graph Embeddings

https://github.com/HanbaekLyu/BCD-DR

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Block majorization-minimization with diminishing radius for constrained nonsmooth nonconvex optimization

https://github.com/HanbaekLyu/SRMM

공식 코드

Stochastic regularized majorization-minimization with weakly convex and multi-convex surrogates

https://github.com/KokiKishimoto/cp_decomposition

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Binarized Knowledge Graph Embeddings

https://github.com/KokiKishimoto/cp_decomposition_alpha

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Binarized Knowledge Graph Embeddings

https://github.com/MaudeLiz/cprnn

공식 코드

A Tensor Decomposition Perspective on Second-order RNNs

https://github.com/Miaoyanwang/Binary-Tensor

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Learning from Binary Multiway Data: Probabilistic Tensor Decomposition and its Statistical Optimality

https://github.com/QWE123665/cICA

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Contrastive independent component analysis

https://github.com/Sean9511/Additive-Tensor-Decomposition-Considering-Structural-Data-Information

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Additive Tensor Decomposition Considering Structural Data Information

https://github.com/Shiran-Yuan/SPTC

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A generalizable framework for low-rank tensor completion with numerical priors

https://github.com/TSTEP99/tensor_decomp_eeg

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Tensor Decomposition of Large-scale Clinical EEGs Reveals Interpretable Patterns of Brain Physiology

https://github.com/TammoR/LogicalFactorisationMachines

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TensOrMachine: Probabilistic Boolean Tensor Decomposition

https://github.com/XiaoFuLab/Quantized-Radio-Map-Estimation-BTD-and-DGM

공식 코드

Quantized Radio Map Estimation Using Tensor and Deep Generative Models

https://github.com/ZichenMiao/Coeff_Tuning

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Coeff-Tuning: A Graph Filter Subspace View for Tuning Attention-Based Large Models

https://github.com/abefrandsen/syntactic-rand-walk

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Understanding Composition of Word Embeddings via Tensor Decomposition

https://github.com/alipay/parameter_inference_efficient_pie

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PIE: a Parameter and Inference Efficient Solution for Large Scale Knowledge Graph Embedding Reasoning

https://github.com/androstj/tensor_rnn

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Tensor Decomposition for Compressing Recurrent Neural Network

https://github.com/apple/ml-sad

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Consistent Collaborative Filtering via Tensor Decomposition

https://github.com/arJaffe/BinaryLatentVariables

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Learning Binary Latent Variable Models: A Tensor Eigenpair Approach

https://github.com/ars2240/asdHBTucker

공식 코드

Conditional Hierarchical Bayesian Tucker Decomposition for Genetic Data Analysis

https://github.com/blueGorae/DynaGAN

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DynaGAN: Dynamic Few-shot Adaptation of GANs to Multiple Domains

https://github.com/chengtaipu/lowrankcnn

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Convolutional neural networks with low-rank regularization

https://github.com/chenyangli-97/nn-bcd

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On Model Compression for Neural Networks: Framework, Algorithm, and Convergence Guarantee

https://github.com/clinicaldatascience/tucker-cnn

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Post-Training Network Compression for 3D Medical Image Segmentation: Reducing Computational Efforts via Tucker Decomposition

https://github.com/clwan/GETF

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Geometric All-Way Boolean Tensor Decomposition

https://github.com/colehawkins/bayesian-tensor-rank-determination

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Towards Compact Neural Networks via End-to-End Training: A Bayesian Tensor Approach with Automatic Rank Determination

https://github.com/cvjena/TensorDecompositions4PINNs

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Functional Tensor Decompositions for Physics-Informed Neural Networks

https://github.com/dagrate/cpoptnet

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Predicting Sparse Clients' Actions with CPOPT-Net in the Banking Environment

https://github.com/danielakuinchtner/cp-mdp

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CP-MDP: A CANDECOMP-PARAFAC Decomposition Approach to Solve a Markov Decision Process Multidimensional Problem

https://github.com/danielecastellana22/tensor-tree-nn

공식 코드

Generalising Recursive Neural Models by Tensor Decomposition

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