Panagiotis Misiakos

e-mail:
Office: CAB H 81.2
Universitätstrasse 6
Zürich, Switzerland

I am a PhD student of Markus Püschel. My research interests include applications of mathematics in Signal Processing and Machine Learning. Currently, I am working on DAG learning methods from a causal Fourier analysis perspective.



Publications

Submitted


Learning DAGs and Root Causes from Time-Series Data
Panagiotis Misiakos and Markus Püschel
submitted for publication
[arXiv]

2025

Learning Time-Varying Graphs from Data with Few Causes
Panagiotis Misiakos and Markus Püschel
to appear in ICASSP 2025

2024

Time-graph
Learning signals and graphs from time-series graph data with few causes
Panagiotis Misiakos, Vedran Mihal, Markus Püschel
Oral presentation in Proc. International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2024.
[pdf] [presentation]

2023

FewCauses
Learning DAGs from Data with Few Root Causes
Panagiotis Misiakos, Chris Wendler, Markus Püschel
Advances in Neural Information Processing Systems 2023.
[pdf] [poster] [short slides]

Learning Gene Regulatory Networks under Few Root Causes assumption
Panagiotis Misiakos, Chris Wendler, Markus Püschel
3rd prize award in GSK.ai CausalBench Challenge 2023, hosted in MLDD workshop ICLR 2023.
[OpenReview] [arXiv] [slides]

2022

Neural Network Approximation based on Hausdorff distance of Tropical Zonotopes
Panagiotis Misiakos, Georgios Smyrnis, Georgios Retsinas, Petros Maragos
In International Conference on Learning Representations (ICLR) 2022.
[pdf] [poster] [slides]

2020

Diagonalizable Shift and Filters for Directed Graphs Based on the Jordan-Chevalley Decomposition
Panagiotis Misiakos, Chris Wendler, Markus Püschel
Proc. International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2020.
[pdf] [poster]

Teaching

Education

Master (M.Eng.) in Engineering.
School of Electrical and Computer Engineering, National Technical University of Athens, Greece.
Thesis (in Greek) supervised by Prof. Petros Maragos.		 November 2021