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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/dsaurus/tensor4d
공식 코드Tensor4D : Efficient Neural 4D Decomposition for High-fidelity Dynamic Reconstruction and Rendering
https://github.com/edwardmagongo/quantum-inspired-model-compression
공식 코드https://github.com/facebookresearch/kbc
공식 코드Canonical Tensor Decomposition for Knowledge Base Completion
https://github.com/fahrbach/subquadratic-kronecker-regression
공식 코드Subquadratic Kronecker Regression with Applications to Tensor Decomposition
https://github.com/fraunhofer-scai/canonical-cnn
공식 코드https://github.com/fwesel/t-krr
공식 코드Large-Scale Learning with Fourier Features and Tensor Decompositions
https://github.com/gaelpouxmedard/simsbm
공식 코드Serialized Interacting Mixed Membership Stochastic Block Model
https://github.com/ganguli-lab/tensorAMP
공식 코드https://github.com/gkazunii/Legendre-tucker-rank-reduction
공식 코드Fast Tucker Rank Reduction for Non-Negative Tensors Using Mean-Field Approximation
https://github.com/gocker/tensorhebb
공식 코드Tensor decomposition of higher-order correlations by nonlinear Hebbian plasticity
https://github.com/grokcv/sdd
공식 코드https://github.com/hachanook/pyinn
공식 코드Interpolating neural network: A novel unification of machine learning and interpolation theory
https://github.com/hadidaneshmand/measure_recovery_codes
공식 코드Polynomial-time Sparse Measure Recovery: From Mean Field Theory to Algorithm Design
https://github.com/hansdesterck/nonlinear-preconditioning-for-optimization
공식 코드https://github.com/haoshu2000/tctnn
공식 코드Guaranteed Multidimensional Time Series Prediction via Deterministic Tensor Completion Theory
https://github.com/higashiguchi-shingo/d-tracker
공식 코드D-Tracker: Modeling Interest Diffusion in Social Activity Tensor Data Streams
https://github.com/hse-cs/migtf
공식 코드Knowledge Graph Completion with Mixed Geometry Tensor Factorization
https://github.com/huttered40/cpr-perf-model
공식 코드https://github.com/iabs-neuro/mango
공식 코드Fast gradient-free activation maximization for neurons in spiking neural networks
https://github.com/imkanghan/nrff
공식 코드Multiscale Tensor Decomposition and Rendering Equation Encoding for View Synthesis
https://github.com/intell-sci-comput/opdf
공식 코드Over-parameterized Student Model via Tensor Decomposition Boosted Knowledge Distillation
https://github.com/iodike/chronokge
공식 코드Temporal Knowledge Graph Reasoning with Low-rank and Model-agnostic Representations
https://github.com/jhood3/allocore
공식 코드The AL$\ell_0$CORE Tensor Decomposition for Sparse Count Data
https://github.com/jianhaoma/function-basis-decomposition
공식 코드Behind the Scenes of Gradient Descent: A Trajectory Analysis via Basis Function Decomposition
https://github.com/jvendrow/multihntf
공식 코드https://github.com/lara-kassab/dynamic-tensor-topic-modeling
공식 코드https://github.com/le-trungnguyen/neurips2024-activationcompression
공식 코드Activation Map Compression through Tensor Decomposition for Deep Learning
https://github.com/liuyuaa/GETD
공식 코드Generalizing Tensor Decomposition for N-ary Relational Knowledge Bases
https://github.com/lpyhdzx/DecoQuant_code
공식 코드Unlocking Data-free Low-bit Quantization with Matrix Decomposition for KV Cache Compression
https://github.com/lsky96/unrolled-tbsca-ad
공식 코드Adaptive Anomaly Detection in Network Flows with Low-Rank Tensor Decompositions and Deep Unrolling
https://github.com/mahito-sugiyama/Legendre-decomposition
공식 코드https://github.com/maxbourdon/mars
공식 코드MARS: Masked Automatic Ranks Selection in Tensor Decompositions
https://github.com/mehmetyamac/mtsnet
공식 코드https://github.com/mhmdjouni/multihu-td-matlab
공식 코드MultiHU-TD: Multifeature Hyperspectral Unmixing Based on Tensor Decomposition
https://github.com/mhmdjouni/multihu-td-python
공식 코드MultiHU-TD: Multifeature Hyperspectral Unmixing Based on Tensor Decomposition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.