Applications of GRID in Clinical Neurophysiology and Electrical Impedance Tomography of Brain Function. - Juan Fritschy; Lior Horesh; David S. Holder; Richard H. Bayford (HealthGrid, 2005)

Design of electrodes and current limits for low frequency electrical impedance tomography of the brain. - O. Gilad; Lior Horesh; David S. Holder (Medical Biol. Eng. Comput., 2007)

Use of anisotropic modelling in electrical impedance tomography; Description of method and preliminary assessment of utility in imaging brain function in the adult human head. - Juan-Felipe P. J. Abascal; Simon R. Arridge; David Atkinson; Raya Horesh; Lorenzo Fabrizi; Marzia De Lucia; Lior Horesh; Richard H. Bayford; David S. Holder (NeuroImage, 2008)

Kalman filtering for compressed sensing. - Dimitri Kanevsky; Avishy Carmi; Lior Horesh; Pini Gurfil; Bhuvana Ramabhadran; Tara N. Sainath (FUSION, 2010)

A Second Order Discretization of Maxwell's Equations in the Quasi-Static Regime on OcTree Grids. - Lior Horesh; Eldad Haber (SIAM J. Sci. Comput., 2011)

Accelerating Hessian-free optimization for Deep Neural Networks by implicit preconditioning and sampling. - Tara N. Sainath; Lior Horesh; Brian Kingsbury; Aleksandr Y. Aravkin; Bhuvana Ramabhadran (ASRU, 2013)

Improving training time of Hessian-free optimization for deep neural networks using preconditioning and sampling. - Tara N. Sainath; Lior Horesh; Brian Kingsbury; Aleksandr Y. Aravkin; Bhuvana Ramabhadran (CoRR, 2013)

Source estimation for wave equations with uncertain parameters. - Sergiy Zhuk; Stephen Moore 003; Alberto Costa Nogueira Jr.; Andrew A. Rawlinson; Tigran T. Tchrakian; Lior Horesh; Aleksandr Y. Aravkin; Albert Akhriev (ECC, 2015)

Semi-discrete Matrix-Free Formulation of 3D Elastic Full Waveform Inversion Modeling. - Stephen Moore 003; Devi Sudheer Chunduri; Sergiy Zhuk; Tigran T. Tchrakian; Ewout van den Berg; Albert Akhriev; Alberto Costa Nogueira Jr.; Andrew A. Rawlinson; Lior Horesh (Euro-Par, 2015)

Community Detection Using Time-Dependent Personalized PageRank. - Haim Avron; Lior Horesh (ICML, 2015)

Image classification using local tensor singular value decompositions. - Elizabeth Newman; Misha E. Kilmer; Lior Horesh (CAMSAP, 2017)

Stable Tensor Neural Networks for Rapid Deep Learning. - Elizabeth Newman; Lior Horesh; Haim Avron; Misha E. Kilmer (CoRR, 2018)

Experimental Design for Nonparametric Correction of Misspecified Dynamical Models. - Gal Shulkind; Lior Horesh; Haim Avron (SIAM/ASA J. Uncertain. Quantification, 2018)

Recurrent Neural Networks in the Eye of Differential Equations. - Murphy Yuezhen Niu; Lior Horesh; Isaac Chuang (CoRR, 2019)

Tensor Graph Convolutional Networks for Prediction on Dynamic Graphs. - Osman Asif Malik; Shashanka Ubaru; Lior Horesh; Misha E. Kilmer; Haim Avron (CoRR, 2019)

Communication over Continuous Quantum Secure Dialogue using Einstein-Podolsky-Rosen States. - Shaokai Lin; Zichuan Wang; Lior Horesh (CoRR, 2019)

Tensor-Tensor Products for Optimal Representation and Compression. - Misha E. Kilmer; Lior Horesh; Haim Avron; Elizabeth Newman (CoRR, 2020)

Symbolic Regression using Mixed-Integer Nonlinear Optimization. - Vernon Austel; Cristina Cornelio; Sanjeeb Dash; Joao Goncalves; Lior Horesh; Tyler R. Josephson; Nimrod Megiddo (CoRR, 2020)

Dynamic graph based epidemiological model for COVID-19 contact tracing data analysis and optimal testing prescription. - Shashanka Ubaru; Lior Horesh; Guy Cohen (CoRR, 2020)

Projection techniques to update the truncated SVD of evolving matrices. - Vassilis Kalantzis; Georgios Kollias; Shashanka Ubaru; Athanasios N. Nikolakopoulos; Lior Horesh; Kenneth L. Clarkson (CoRR, 2020)

Quantum-Inspired Algorithms from Randomized Numerical Linear Algebra. - Nadiia Chepurko; Kenneth L. Clarkson; Lior Horesh; David P. Woodruff (CoRR, 2020)

Denoising quantum states with Quantum Autoencoders - Theory and Applications. - Tom Achache; Lior Horesh; John A. Smolin (CoRR, 2020)

Thinking Fast and Slow in AI. - Grady Booch; Francesco Fabiano; Lior Horesh; Kiran Kate; Jonathan Lenchner; Nick Linck; Andrea Loreggia; Keerthiram Murugesan; Nicholas Mattei; Francesca Rossi 001; Biplav Srivastava (AAAI, 2021)

Decentralized Policy Gradient Descent Ascent for Safe Multi-Agent Reinforcement Learning. - Songtao Lu; Kaiqing Zhang; Tianyi Chen; Tamer Basar; Lior Horesh (AAAI, 2021)

Epistemic Planning in a Fast and Slow Setting. - Francesco Fabiano; Marianna Bergamaschi Ganapini; Lior Horesh; Andrea Loreggia; Keerthiram Murugesan; Vishal Pallagani; Francesca Rossi 001; Biplav Srivastava (TFSOCTAI@AAAI Fall Symposium, 2021)

Combining Fast and Slow Thinking for Human-like and Efficient Navigation in Constrained Environments. - Marianna Bergamaschi Ganapini; Murray Campbell; Francesco Fabiano; Lior Horesh; Jonathan Lenchner; Andrea Loreggia; Nicholas Mattei; Francesca Rossi 001; Biplav Srivastava; Kristen Brent Venable (TFSOCTAI@AAAI Fall Symposium, 2021)

Solving sparse linear systems with approximate inverse preconditioners on analog devices. - Vasileios Kalantzis; Anshul Gupta; Lior Horesh; Tomasz Nowicki; Mark S. Squillante; Chai Wah Wu; Tayfun Gokmen; Haim Avron (HPEC, 2021)

Sparse Graph Based Sketching for Fast Numerical Linear Algebra. - Dong Hu; Shashanka Ubaru; Alex Gittens; Kenneth L. Clarkson; Lior Horesh; Vassilis Kalantzis (ICASSP, 2021)

Training Logical Neural Networks by Primal-Dual Methods for Neuro-Symbolic Reasoning. - Songtao Lu; Naweed Khan; Ismail Yunus Akhalwaya; Ryan Riegel; Lior Horesh; Alexander G. Gray (ICASSP, 2021)

Projection techniques to update the truncated SVD of evolving matrices with applications. - Vasileios Kalantzis; Georgios Kollias; Shashanka Ubaru; Athanasios N. Nikolakopoulos; Lior Horesh; Kenneth L. Clarkson (ICML, 2021)

Dynamic Graph Convolutional Networks Using the Tensor M-Product. - Osman Asif Malik; Shashanka Ubaru; Lior Horesh; Misha E. Kilmer; Haim Avron (SDM, 2021)

Fast randomized non-Hermitian eigensolver based on rational filtering and matrix partitioning. - Vassilis Kalantzis; Yuanzhe Xi; Lior Horesh (CoRR, 2021)

Solving sparse linear systems with approximate inverse preconditioners on analog devices. - Vasileios Kalantzis; Anshul Gupta; Lior Horesh; Tomasz Nowicki; Mark S. Squillante; Chai Wah Wu (CoRR, 2021)

E-PDDL: A Standardized Way of Defining Epistemic Planning Problems. - Francesco Fabiano; Biplav Srivastava; Jonathan Lenchner; Lior Horesh; Francesca Rossi 001; Marianna Bergamaschi Ganapini (CoRR, 2021)

Quantum Topological Data Analysis with Linear Depth and Exponential Speedup. - Shashanka Ubaru; Ismail Yunus Akhalwaya; Mark S. Squillante; Kenneth L. Clarkson; Lior Horesh (CoRR, 2021)

Integration of Data and Theory for Accelerated Derivable Symbolic Discovery. - Cristina Cornelio; Sanjeeb Dash; Vernon Austel; Tyler R. Josephson; Joao Goncalves; Kenneth L. Clarkson; Nimrod Megiddo; Bachir El Khadir; Lior Horesh (CoRR, 2021)

Dynamic graph and polynomial chaos based models for contact tracing data analysis and optimal testing prescription. - Shashanka Ubaru; Lior Horesh; Guy Cohen (J. Biomed. Informatics, 2021)

Fast Randomized Non-Hermitian Eigensolvers Based on Rational Filtering and Matrix Partitioning. - Vassilis Kalantzis; Yuanzhe Xi; Lior Horesh (SIAM J. Sci. Comput., 2021)

Decentralized Bilevel Optimization for Personalized Client Learning. - Songtao Lu; Xiaodong Cui; Mark S. Squillante; Brian Kingsbury; Lior Horesh (ICASSP, 2022)

Quantum-Inspired Algorithms from Randomized Numerical Linear Algebra. - Nadiia Chepurko; Kenneth L. Clarkson; Lior Horesh; Honghao Lin; David P. Woodruff (ICML, 2022)

Thinking Fast and Slow in AI: The Role of Metacognition. - Marianna Bergamaschi Ganapini; Murray Campbell; Francesco Fabiano; Lior Horesh; Jon Lenchner; Andrea Loreggia; Nicholas Mattei; Francesca Rossi 001; Biplav Srivastava; Kristen Brent Venable (LOD (2), 2022)

Combining Fast and Slow Thinking for Human-like and Efficient Decisions in Constrained Environments. - Marianna Bergamaschi Ganapini; Murray Campbell; Francesco Fabiano; Lior Horesh; Jonathan Lenchner; Andrea Loreggia; Nicholas Mattei; Francesca Rossi 001; Biplav Srivastava; Kristen Brent Venable (NeSy, 2022)

A Stochastic Linearized Augmented Lagrangian Method for Decentralized Bilevel Optimization. - Songtao Lu; Siliang Zeng; Xiaodong Cui; Mark S. Squillante; Lior Horesh; Brian Kingsbury; Jia Liu 002; Mingyi Hong 001 (NeurIPS, 2022)

Overcoming Catastrophic Forgetting via Direction-Constrained Optimization. - Yunfei Teng; Anna Choromanska; Murray Campbell; Songtao Lu; Parikshit Ram; Lior Horesh (ECML/PKDD (1), 2022)

Distributed adversarial training to robustify deep neural networks at scale. - Gaoyuan Zhang; Songtao Lu; Yihua Zhang; Xiangyi Chen; Pin-Yu Chen; Quanfu Fan; Lee Martie; Lior Horesh; Mingyi Hong 001; Sijia Liu 001 (UAI, 2022)

Combining Fast and Slow Thinking for Human-like and Efficient Navigation in Constrained Environments. - Marianna Bergamaschi Ganapini; Murray Campbell; Francesco Fabiano; Lior Horesh; Jon Lenchner; Andrea Loreggia; Nicholas Mattei; Taher Rahgooy; Francesca Rossi 001; Biplav Srivastava; Kristen Brent Venable (CoRR, 2022)

Efficient Quantum Computation of the Fermionic Boundary Operator. - Ismail Yunus Akhalwaya; Yang-Hui He; Lior Horesh; Vishnu Jejjala; William Kirby; Kugendran Naidoo; Shashanka Ubaru (CoRR, 2022)

PCENet: High Dimensional Surrogate Modeling for Learning Uncertainty. - Paz Fink Shustin; Shashanka Ubaru; Vasileios Kalantzis; Lior Horesh; Haim Avron (CoRR, 2022)

Towards Quantum Advantage on Noisy Quantum Computers. - Ismail Yunus Akhalwaya; Shashanka Ubaru; Kenneth L. Clarkson; Mark S. Squillante; Vishnu Jejjala; Yang-Hui He; Kugendran Naidoo; Vasileios Kalantzis; Lior Horesh (CoRR, 2022)

Creating quantum-resistant classical-classical OWFs from quantum-classical OWFs. - Wei Zheng Teo; Marco Carmosino; Lior Horesh (CoRR, 2022)

From String Detection to Orthogonal Vector Problem. - Yunhao Wang; Tianyuan Zheng; Lior Horesh (CoRR, 2022)

Bayesian Experimental Design for Symbolic Discovery. - Kenneth L. Clarkson; Cristina Cornelio; Sanjeeb Dash; Joao Goncalves; Lior Horesh; Nimrod Megiddo (CoRR, 2022)

Plansformer: Generating Symbolic Plans using Transformers. - Vishal Pallagani; Bharath Muppasani; Keerthiram Murugesan; Francesca Rossi 001; Lior Horesh; Biplav Srivastava; Francesco Fabiano; Andrea Loreggia (CoRR, 2022)

On Quantum Algorithms for Random Walks in the Nonnegative Quarter Plane. - Vasileios Kalantzis; Mark S. Squillante; Shashanka Ubaru; Lior Horesh (SIGMETRICS Perform. Evaluation Rev., 2022)

Value-based Fast and Slow AI Nudging. - Marianna Bergamaschi Ganapini; Francesco Fabiano; Lior Horesh; Andrea Loreggia; Nicholas Mattei; Keerthiram Murugesan; Vishal Pallagani; Francesca Rossi 001; Biplav Srivastava; Kristen Brent Venable (ETHAICS@IJCAI, 2023)

Solving Sparse Linear Systems via Flexible GMRES with In-Memory Analog Preconditioning. - Vasileios Kalantzis; Mark S. Squillante; Chai Wah Wu; Anshul Gupta; Shashanka Ubaru; Tayfun Gokmen; Lior Horesh (HPEC, 2023)

Plansformer Tool: Demonstrating Generation of Symbolic Plans Using Transformers. - Vishal Pallagani; Bharath Muppasani; Biplav Srivastava; Francesca Rossi 001; Lior Horesh; Keerthiram Murugesan; Andrea Loreggia; Francesco Fabiano; Rony Joseph; Yathin Kethepalli (IJCAI, 2023)

Fast and Slow Planning. - Francesco Fabiano; Vishal Pallagani; Marianna Bergamaschi Ganapini; Lior Horesh; Andrea Loreggia; Keerthiram Murugesan; Francesca Rossi 001; Biplav Srivastava (CoRR, 2023)

Understanding the Capabilities of Large Language Models for Automated Planning. - Vishal Pallagani; Bharath Muppasani; Keerthiram Murugesan; Francesca Rossi 001; Biplav Srivastava; Lior Horesh; Francesco Fabiano; Andrea Loreggia (CoRR, 2023)

AI Hilbert: From Data and Background Knowledge to Automated Scientific Discovery. - Ryan Cory-Wright; Bachir El Khadir; Cristina Cornelio; Sanjeeb Dash; Lior Horesh (CoRR, 2023)

Stable iterative refinement algorithms for solving linear systems. - Chai Wah Wu; Mark S. Squillante; Vasileios Kalantzis; Lior Horesh (CoRR, 2023)

Enhanced algebraic substructuring for symmetric generalized eigenvalue problems. - Vassilis Kalantzis; Lior Horesh (Numer. Linear Algebra Appl., 2023)

Asynchronous Randomized Trace Estimation. - Vasileios Kalantzis; Shashanka Ubaru; Chai Wah Wu; Georgios Kollias; Lior Horesh (AISTATS, 2024)

On the Prospects of Incorporating Large Language Models (LLMs) in Automated Planning and Scheduling (APS). - Vishal Pallagani; Bharath C. Muppasani; Kaushik Roy 009; Francesco Fabiano; Andrea Loreggia; Keerthiram Murugesan; Biplav Srivastava; Francesca Rossi 001; Lior Horesh; Amit P. Sheth (ICAPS, 2024)

Topological data analysis on noisy quantum computers. - Ismail Yunus Akhalwaya; Shashanka Ubaru; Kenneth L. Clarkson; Mark S. Squillante; Vishnu Jejjala; Yang-Hui He; Kugendran Naidoo; Vasileios Kalantzis; Lior Horesh (ICLR, 2024)

Counting Triangles of Graphs via Matrix Partitioning. - Georgios Kollias; Vassilis Kalantzis; Lior Horesh; Shashanka Ubaru; Panagiotis A. Traganitis (MLSP, 2024)

Single-pass top-N subgraph centrality of graphs via subspace projections. - Vassilis Kalantzis; Georgios Kollias; Shashanka Ubaru; Naoki Abe; Lior Horesh (J. Complex Networks, 2024)

Multi-Function Multi-Way Analog Technology for Sustainable Machine Intelligence Computation. - Vassilis Kalantzis; Mark S. Squillante; Shashanka Ubaru; Tayfun Gokmen; Chai Wah Wu; Anshul Gupta; Haim Avron; Tomasz Nowicki; Malte J. Rasch; O. Murat Onen; Vanessa López-Marrero; Effendi Leobandung; et al. (CoRR, 2024)

Randomized linear solvers for computational architectures with straggling workers. - Vassilis Kalantzis; Yuanzhe Xi; Lior Horesh; Yousef Saad (CoRR, 2024)

Regenerative Ulam-von Neumann Algorithm: An Innovative Markov chain Monte Carlo Method for Matrix Inversion. - Soumyadip Ghosh; Lior Horesh; Vassilis Kalantzis; Yingdong Lu; Tomasz Nowicki (CoRR, 2024)

Quantifying artificial intelligence through algebraic generalization. - Takuya Ito; Murray Campbell; Lior Horesh; Tim Klinger; Parikshit Ram (CoRR, 2024)

Stable tensor neural networks for efficient deep learning. - Elizabeth Newman; Lior Horesh; Haim Avron; Misha E. Kilmer (Frontiers Big Data, 2024)

A Rational Filtering Algorithm for Sequences of Shifted Symmetric Linear Systems with Applications to Frequency Response Analysis. - Anthony P. Austin; Lior Horesh; Vassilis Kalantzis (SIAM J. Sci. Comput., 2024)

Epigraph Based Multilevel Optimization (EMO) for Enhancing Chain-of-Thought Reasoning Capabilities. - Songtao Lu; Yanna Ding; Lior Horesh; Jianxi Gao; Malik Magdon-Ismail (ICASSP, 2025)

On the variance of Schatten p-norm estimation with Gaussian sketching matrices. - Lior Horesh; Vasileios Kalantzis; Yingdong Lu; Tomasz Nowicki (Monte Carlo Methods Appl., 2025)

Multivariate Trace Estimation Using Quantum State Space Linear Algebra. - Liron Mor-Yosef; Shashanka Ubaru; Lior Horesh; Haim Avron (SIAM J. Matrix Anal. Appl., 2025)

SynPAT: A System for Generating Synthetic Physical Theories with Data. - Jonathan Lenchner; Karan Srivastava; Joao Goncalves; Lior Horesh (CoRR, 2025)

Finding Clustering Algorithms in the Transformer Architecture. - Kenneth L. Clarkson; Lior Horesh; Takuya Ito; Charlotte Park; Parikshit Ram (CoRR, 2025)

Stable iterative refinement for solving linear systems with inaccurate computation. - Chai Wah Wu; Mark S. Squillante; Vassilis Kalantzis; Lior Horesh (J. Comput. Appl. Math., 2026)