Maximum likelihood and polynomial system solving. - Kim Batselier; Bart De Moor (BIBM Workshops, 2010)

maximum likelihood estimation and polynomial system solving. - Kim Batselier; Philippe Dreesen; Bart De Moor (ESANN, 2012)

Weighted/Structured Total Least Squares problems and polynomial system solving. - Philippe Dreesen; Kim Batselier; Bart De Moor (ESANN, 2012)

Joint Regression and Linear Combination of Time Series for Optimal Prediction. - Dries Geebelen; Kim Batselier; Philippe Dreesen; Marco Signoretto; Johan A. K. Suykens; Bart De Moor; Joos Vandewalle (ESANN, 2012)

The Geometry of Multivariate Polynomial Division and Elimination. - Kim Batselier; Philippe Dreesen; Bart De Moor (SIAM J. Matrix Anal. Appl., 2013)

An Efficient Two-level DC Operating Points Finder for Transistor Circuits. - Jian Deng; Kim Batselier; Yang Zhang; Ngai Wong 001 (DAC, 2014)

A novel linear algebra method for the determination of periodic steady states of nonlinear oscillators. - Haotian Liu; Kim Batselier; Ngai Wong 001 (ICCAD, 2014)

A fast recursive orthogonalization scheme for the Macaulay matrix. - Kim Batselier; Philippe Dreesen; Bart De Moor (J. Comput. Appl. Math., 2014)

The Canonical Decomposition of Cnd and Numerical Gröbner and Border Bases. - Kim Batselier; Philippe Dreesen; Bart De Moor (SIAM J. Matrix Anal. Appl., 2014)

An adaptive dynamical low-rank tensor approximation scheme for fast circuit simulation. - Kim Batselier; Quan Chen 007; Ngai Wong 001 (ASICON, 2015)

STAVES: Speedy Tensor-Aided Volterra-Based Electronic Simulator. - Haotian Liu; Xiaoyan Y. Z. Xiong; Kim Batselier; Lijun Jiang; Luca Daniel; Ngai Wong 001 (ICCAD, 2015)

A Constructive Algorithm for Decomposing a Tensor into a Finite Sum of Orthonormal Rank-1 Terms. - Kim Batselier; Haotian Liu; Ngai Wong 001 (SIAM J. Matrix Anal. Appl., 2015)

STORM: A nonlinear model order reduction method via symmetric tensor decomposition. - Jian Deng; Haotian Liu; Kim Batselier; Yu-Kwong Kwok; Ngai Wong 001 (ASP-DAC, 2016)

A tensor-based volterra series black-box nonlinear system identification and simulation framework. - Kim Batselier; Zhongming Chen; Haotian Liu; Ngai Wong 001 (ICCAD, 2016)

Computing the state difference equations for discrete overdetermined linear systems. - Kim Batselier; Ngai Wong 001 (Autom., 2016)

Tensor Train alternating linear scheme for MIMO Volterra system identification. - Kim Batselier; Zhongming Chen; Ngai Wong 001 (CoRR, 2016)

Symmetric tensor decomposition by an iterative eigendecomposition algorithm. - Kim Batselier; Ngai Wong 001 (J. Comput. Appl. Math., 2016)

Tensor-network-based predistorter design for multiple-input multiple-output nonlinear systems. - Cong Chen 003; Kim Batselier; Mihai Telescu; Stéphane Azou; Noël Tanguy; Ngai Wong 001 (ASICON, 2017)

An efficient homotopy-based Poincaré-Lindstedt method for the periodic steady-state analysis of nonlinear autonomous oscillators. - Zhongming Chen; Kim Batselier; Haotian Liu; Ngai Wong 001 (ASP-DAC, 2017)

A Tensor Network Kalman filter with an application in recursive MIMO Volterra system identification. - Kim Batselier; Zhongming Chen; Ngai Wong 001 (Autom., 2017)

Tensor Network alternating linear scheme for MIMO Volterra system identification. - Kim Batselier; Zhongming Chen; Ngai Wong 001 (Autom., 2017)

Inverse multivariate polynomial root-finding: Numerical implementations of the affine and projective Buchberger-Möller algorithm. - Kim Batselier; Ngai Wong 001 (J. Comput. Appl. Math., 2017)

A constructive arbitrary-degree Kronecker product decomposition of tensors. - Kim Batselier; Ngai Wong 001 (Numer. Linear Algebra Appl., 2017)

Tensor Computation: A New Framework for High-Dimensional Problems in EDA. - Zheng Zhang 005; Kim Batselier; Haotian Liu; Luca Daniel; Ngai Wong 001 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2017)

Tensor network subspace identification of polynomial state space models. - Kim Batselier; Ching Yun Ko; Ngai Wong 001 (Autom., 2018)

Matrix output extension of the tensor network Kalman filter with an application in MIMO Volterra system identification. - Kim Batselier; Ngai Wong 001 (Autom., 2018)

Fast and Accurate Tensor Completion with Tensor Trains: A System Identification Approach. - Ching Yun Ko; Kim Batselier; Wenjian Yu; Ngai Wong 001 (CoRR, 2018)

Multidimensional Realization Theory and Polynomial System Solving. - Philippe Dreesen; Kim Batselier; Bart De Moor (CoRR, 2018)

The trouble with tensor ring decompositions. - Kim Batselier (CoRR, 2018)

Deep Compression of Sum-Product Networks on Tensor Networks. - Ching Yun Ko; Cong Chen 003; Yuke Zhang; Kim Batselier; Ngai Wong 001 (CoRR, 2018)

Multidimensional realisation theory and polynomial system solving. - Philippe Dreesen; Kim Batselier; Bart De Moor (Int. J. Control, 2018)

Computing Low-Rank Approximations of Large-Scale Matrices with the Tensor Network Randomized SVD. - Kim Batselier; Wenjian Yu; Luca Daniel; Ngai Wong 001 (SIAM J. Matrix Anal. Appl., 2018)

Parallelized Tensor Train Learning of Polynomial Classifiers. - Zhongming Chen; Kim Batselier; Johan A. K. Suykens; Ngai Wong 001 (IEEE Trans. Neural Networks Learn. Syst., 2018)

Extended Kalman Filtering with Low-Rank Tensor Networks for MIMO Volterra System Identification. - Kim Batselier; Ching-Yun Ko; Ngai Wong 001 (CDC, 2019)

Tensor Network Kalman Filter for LTI Systems. - Daniel Gedon; Pieter Piscaer; Kim Batselier; Carlas S. Smith; Michel Verhaegen (EUSIPCO, 2019)

Matrix Product Operator Restricted Boltzmann Machines. - Cong Chen 003; Kim Batselier; Ching-Yun Ko; Ngai Wong 001 (IJCNN, 2019)

A Support Tensor Train Machine. - Cong Chen 003; Kim Batselier; Ching-Yun Ko; Ngai Wong 001 (IJCNN, 2019)

MERACLE: Constructive layer-wise conversion of a Tensor Train into a MERA. - Kim Batselier; Andrzej Cichocki; Ngai Wong 001 (CoRR, 2019)

Nonlinear system identification with regularized Tensor Network B-splines. - Ridvan Karagoz; Kim Batselier (Autom., 2020)

Fast and Accurate Tensor Completion With Total Variation Regularized Tensor Trains. - Ching-Yun Ko; Kim Batselier; Luca Daniel; Wenjian Yu; Ngai Wong 001 (IEEE Trans. Image Process., 2020)

Deep Model Compression and Inference Speedup of Sum-Product Networks on Tensor Trains. - Ching-Yun Ko; Cong Chen 003; Zhuolun He; Yuke Zhang; Kim Batselier; Ngai Wong 001 (IEEE Trans. Neural Networks Learn. Syst., 2020)

Large-Scale Learning with Fourier Features and Tensor Decompositions. - Frederiek Wesel; Kim Batselier (NeurIPS, 2021)

Tensor Network Kalman Filtering for Large-Scale LS-SVMs. - Maximilian Lucassen; Johan A. K. Suykens; Kim Batselier (CoRR, 2021)

Towards Green AI with tensor networks - Sustainability and innovation enabled by efficient algorithms. - Eva Memmel; Clara Menzen; Jetze Schuurmans; Frederiek Wesel; Kim Batselier (CoRR, 2022)

Faster tensor train decomposition for sparse data. - Lingjie Li; Wenjian Yu; Kim Batselier (J. Comput. Appl. Math., 2022)

Kernelized support tensor train machines. - Cong Chen 003; Kim Batselier; Wenjian Yu; Ngai Wong 001 (Pattern Recognit., 2022)

Alternating Linear Scheme in a Bayesian Framework for Low-Rank Tensor Approximation. - Clara Menzen; Manon Kok; Kim Batselier (SIAM J. Sci. Comput., 2022)

Tensor-based Kernel Machines with Structured Inducing Points for Large and High-Dimensional Data. - Frederiek Wesel; Kim Batselier (AISTATS, 2023)

Enabling Large-Scale Probabilistic Seizure Detection with a Tensor-Network Kalman Filter for LS-SVM. - Seline J. S. de Rooij; Kim Batselier; Borbála Hunyadi (ICASSP Workshops, 2023)

How Informative is the Approximation Error from Tensor Decomposition for Neural Network Compression? - Jetze Schuurmans; Kim Batselier; Julian F. P. Kooij (ICLR, 2023)

Projecting basis functions with tensor networks for Gaussian process regression. - Clara Menzen; Eva Memmel; Kim Batselier; Manon Kok (CoRR, 2023)

Quantized Fourier and Polynomial Features for more Expressive Tensor Network Models. - Frederiek Wesel; Kim Batselier (AISTATS, 2024)

Position: Tensor Networks are a Valuable Asset for Green AI. - Eva Memmel; Clara Menzen; Jetze Schuurmans; Frederiek Wesel; Kim Batselier (ICML, 2024)

Constructing structured tensor priors for Bayesian inverse problems. - Kim Batselier (CoRR, 2024)

Tensor network square root Kalman filter for online Gaussian process regression. - Clara Menzen; Manon Kok; Kim Batselier (CoRR, 2024)

A Kernelizable Primal-Dual Formulation of the Multilinear Singular Value Decomposition. - Frederiek Wesel; Kim Batselier (CoRR, 2024)

Tensor Network Based Feature Learning Model. - Albert Saiapin; Kim Batselier (AISTATS, 2025)

Tensor Network-Constrained Kernel Machines as Gaussian Processes. - Frederiek Wesel; Kim Batselier (AISTATS, 2025)

A Divide-and-conquer Approach for Sparse Recovery in High Dimensions. - Aron Bevelander; Kim Batselier; Nitin Jonathan Myers (ICASSP, 2025)

Low-dimensional Subspace Regularization through Structured Tensor Priors. - Kim Batselier (SIAM/ASA J. Uncertain. Quantification, 2025)

Interpretable Bayesian Tensor Network Kernel Machines with Automatic Rank and Feature Selection. - Afra Kilic; Kim Batselier (CoRR, 2025)