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

Time-graph
Learning signals and graphs from time-series graph data with few causes
Panagiotis Misiakos, Vedran Mihal, Markus Püschel
submitted for publication

FewCauses
Learning DAGs from Data with Few Root Causes
Panagiotis Misiakos, Chris Wendler, Markus Püschel
accepted at NeurIPS 2023 [arXiv]

2023

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) [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) [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