Tensor Network Learning with PyTorch
MUSCO: MUlti-Stage COmpression of neural networks
Provides compile-time contraction pattern analysis to determine optimal tensor operation to perform.
Tensor decomposition implemented in TensorFlow
Python Tensor Toolbox
OnLine Low-rank Subspace tracking by TEnsor CP Decomposition in Matlab: Version 1.0.1
[IEEE TKDE 2023] A list of up-to-date papers on streaming tensor decomposition, tensor tracking, dynamic tensor analysis
An implementation of various tensor-based decomposition for NN & RNN parameters
An implementation of various tensor-based decomposition for NN & RNN parameters
[IEEE ICASSP 2021] "A fast randomized adaptive CP decomposition for streaming tensors". In 46th IEEE International Conference on Acoustics, Speech, & Signal Processing, 2021.
Implementation of TuckERT [Shao,Yang,Zhang et al.] [arXiv:2011.07751] [2020]
MUSCO: Multi-Stage COmpression of neural networks
Tensor on Spark.
[ICML2025] Canonical Rank Adaptation: An Efficient Fine-Tuning Strategy for Vision Transformers
A list of up-to-date and on-going papers on streaming,adaptive,online,incremental tensor decompositions, tensor tracking, dynamic tensor analysis
[Patterns 2023] Tracking Online Low-Rank Approximations of Higher-Order Incomplete Streaming Tensors. In Patterns (Cell Press) 2023.
Flip-graph search (in 𝔽₂ or 𝔽₃) for low-rank CP decompositions, with a focus on structured matrix multiplication.
Code for our preprint paper titled "Sampling-Based Decomposition Algorithms for Arbitrary Tensor Networks"
"Tensor Decomposition to Capture Spatiotemporal Patterns of Coupled Oscillator and Opinion Dynamics" by Agam Goyal and Hanbaek Lyu
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