5 citations · 8 across the 3 of their papers we have counts for
4 papers
SpinSVAR: Estimating Structural Vector Autoregression Assuming Sparse Input
Panagiotis Misiakos, Markus Püschel
We introduce SpinSVAR, a novel method for estimating a structural vector autoregression (SVAR) from time-series data under sparse input assumption. Unlike prior approaches using Ga…
TropNNC: Structured Neural Network Compression Using Tropical Geometry
Konstantinos Fotopoulos, Petros Maragos, Panagiotis Misiakos
We present TropNNC, a framework for compressing neural networks with linear and convolutional layers and ReLU-type activations using tropical geometry. By representing a network's…
The CausalBench challenge: A machine learning contest for gene network inference from single-cell perturbation data
Mathieu Chevalley, Jacob Sackett-Sanders, Yusuf Roohani +15
In drug discovery, mapping interactions between genes within cellular systems is a crucial early step. Such maps are not only foundational for understanding the molecular mechanism…
Learning DAGs from Data with Few Root Causes
Panagiotis Misiakos, Chris Wendler, Markus Püschel
We present a novel perspective and algorithm for learning directed acyclic graphs (DAGs) from data generated by a linear structural equation model (SEM). First, we show that a line…