Sebastian Lehner

According to our database, Sebastian Lehner authored at least 10 papers between 2021 and 2025.

Collaborative distances:

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

2025

Scalable Discrete Diffusion Samplers: Combinatorial Optimization and Statistical Physics.

Sebastian Sanokowski, Wilhelm Berghammer, Martin Ennemoser, Haoyu Peter Wang, Sepp Hochreiter, Sebastian Lehner

CoRR, February, 2025

Derivation of characteristic physioclimatic regions through density-based spatial clustering of high-dimensional data.

Sebastian Lehner, Katharina Enigl, Matthias Schlögl

Environ. Model. Softw., 2025

2024

A Diffusion Model Framework for Unsupervised Neural Combinatorial Optimization.

Sebastian Sanokowski, Sepp Hochreiter, Sebastian Lehner

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Improved machine learning algorithm for predicting ground state properties.

Laura Lewis, Hsin-Yuan Huang, Viet T. Tran, Sebastian Lehner, Richard Kueng, John Preskill

CoRR, 2023

Variational Annealing on Graphs for Combinatorial Optimization.

Sebastian Sanokowski, Wilhelm Berghammer, Sepp Hochreiter, Sebastian Lehner

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Boundary Graph Neural Networks for 3D Simulations.

Andreas Mayr, Sebastian Lehner, Arno Mayrhofer, Christoph Kloss, Sepp Hochreiter, Johannes Brandstetter

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Residual Neural Networks for the Prediction of Planetary Collision Outcomes.

Philip M. Winter, Christoph Burger, Sebastian Lehner, Johannes Kofler, Thomas I. Maindl, Christoph M. Schäfer

CoRR, 2022

History Compression via Language Models in Reinforcement Learning.

Fabian Paischer, Thomas Adler, Vihang Patil, Angela Bitto-Nemling, Markus Holzleitner, Sebastian Lehner, Hamid Eghbal-Zadeh, Sepp Hochreiter

Proceedings of the International Conference on Machine Learning, 2022

Few-Shot Learning by Dimensionality Reduction in Gradient Space.

Martin Gauch, Maximilian Beck, Thomas Adler, Dmytro Kotsur, Stefan Fiel, Hamid Eghbal-zadeh, Johannes Brandstetter, Johannes Kofler, Markus Holzleitner, Werner Zellinger, Daniel Klotz, Sepp Hochreiter, Sebastian Lehner

Proceedings of the Conference on Lifelong Learning Agents, 2022

2021

Learning 3D Granular Flow Simulations.

Andreas Mayr, Sebastian Lehner, Arno Mayrhofer, Christoph Kloss, Sepp Hochreiter, Johannes Brandstetter

CoRR, 2021