Andrei Ivanov

According to our database, Andrei Ivanov authored at least 14 papers between 2018 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

The Universe in the Trap: the Hénon-Heiles Astrophysics Model for the Dynamics in Ion Traps with Inhomogeneity.

Semyon Rudyi, Dmitrii Shcherbinin, Andrei Ivanov

Int. J. Bifurc. Chaos, January, 2026

2025

PerfDojo: Automated ML Library Generation for Heterogeneous Architectures.

Andrei Ivanov, Siyuan Shen, Gioele Gottardo, Marcin Chrapek, Afif Boudaoud, Timo Schneider, Luca Benini, Torsten Hoefler

Proceedings of the International Conference for High Performance Computing, 2025

2024

TMPNN: High-Order Polynomial Regression Based on Taylor Map Factorization.

Andrei Ivanov, Stefan Maria Ailuro

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Cached Operator Reordering: A Unified View for Fast GNN Training.

Julia Bazinska, Andrei Ivanov, Tal Ben-Nun, Nikoli Dryden, Maciej Besta, Siyuan Shen, Torsten Hoefler

CoRR, 2023

STen: Productive and Efficient Sparsity in PyTorch.

Andrei Ivanov, Nikoli Dryden, Tal Ben-Nun, Saleh Ashkboos, Torsten Hoefler

CoRR, 2023

SAGE: Software-based Attestation for GPU Execution.

Andrei Ivanov, Benjamin Rothenberger, Arnaud Dethise, Marco Canini, Torsten Hoefler, Adrian Perrig

Proceedings of the 2023 USENIX Annual Technical Conference, 2023

VENOM: A Vectorized N: M Format for Unleashing the Power of Sparse Tensor Cores.

Roberto L. Castro, Andrei Ivanov, Diego Andrade, Tal Ben-Nun, Basilio B. Fraguela, Torsten Hoefler

Proceedings of the International Conference for High Performance Computing, 2023

2022

A data-centric optimization framework for machine learning.

Oliver Rausch, Tal Ben-Nun, Nikoli Dryden, Andrei Ivanov, Shigang Li, Torsten Hoefler

Proceedings of the ICS '22: 2022 International Conference on Supercomputing, Virtual Event, June 28, 2022

2021

Data Movement Is All You Need: A Case Study on Optimizing Transformers.

Andrei Ivanov, Nikoli Dryden, Tal Ben-Nun, Shigang Li, Torsten Hoefler

Proceedings of the Fourth Conference on Machine Learning and Systems, 2021

2020

Physics-Based Deep Neural Networks for Beam Dynamics in Charged Particle Accelerators.

Andrei Ivanov, Ilya Agapov

CoRR, 2020

Physics-based polynomial neural networks for one-shot learning of dynamical systems from one or a few samples.

Andrei Ivanov, Uwe Iben, Anna Golovkina

CoRR, 2020

Polynomial Neural Networks and Taylor Maps for Dynamical Systems Simulation and Learning.

Andrei Ivanov, Anna Golovkina, Uwe Iben

Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

2019

Matrix Lie Maps and Neural Networks for Solving Differential Equations.

Andrei Ivanov, Sergei Andrianov

CoRR, 2019

2018

Lie Transform Based Polynomial Neural Networks for Dynamical Systems Simulation and Identification.

Andrei Ivanov, Sergei Andrianov, Alena Sholokhova

CoRR, 2018