no code implementations • 29 May 2024 • Ioannis Emiris, Dimitris Fotakis, Giorgos Giannopoulos, Dimitrios Gunopulos, Loukas Kavouras, Kleopatra Markou, Eleni Psaroudaki, Dimitrios Rontogiannis, Dimitris Sacharidis, Nikolaos Theologitis, Dimitrios Tomaras, Konstantinos Tsopelas
Counterfactual explanations have emerged as an important tool to understand, debug, and audit complex machine learning models.
no code implementations • 20 Apr 2024 • Kleopatra Markou, Dimitrios Tomaras, Vana Kalogeraki, Dimitrios Gunopulos
The imminent need to interpret the output of a Machine Learning model with counterfactual (CF) explanations - via small perturbations to the input - has been notable in the research community.
no code implementations • 12 Jan 2023 • Nikolaos Zygouras, Nikolaos Panagiotou, Yang Li, Dimitrios Gunopulos, Leonidas Guibas
Travel time estimation is a critical task, useful to many urban applications at the individual citizen and the stakeholder level.
no code implementations • 12 Jan 2023 • Nikolaos Zygouras, Dimitrios Gunopulos
In this paper we present a deep learning framework that encodes the sparse recent traffic information and forecasts the future traffic condition.
no code implementations • 1 Mar 2022 • Mary Touranakou, Nadezda Chernyavskaya, Javier Duarte, Dimitrios Gunopulos, Raghav Kansal, Breno Orzari, Maurizio Pierini, Thiago Tomei, Jean-Roch Vlimant
We study how to use Deep Variational Autoencoders for a fast simulation of jets of particles at the LHC.
2 code implementations • NeurIPS 2021 • Raghav Kansal, Javier Duarte, Hao Su, Breno Orzari, Thiago Tomei, Maurizio Pierini, Mary Touranakou, Jean-Roch Vlimant, Dimitrios Gunopulos
We propose JetNet as a novel point-cloud-style dataset for the ML community to experiment with, and set MPGAN as a benchmark to improve upon for future generative models.
2 code implementations • 30 Nov 2020 • Raghav Kansal, Javier Duarte, Breno Orzari, Thiago Tomei, Maurizio Pierini, Mary Touranakou, Jean-Roch Vlimant, Dimitrios Gunopulos
We develop a graph generative adversarial network to generate sparse data sets like those produced at the CERN Large Hadron Collider (LHC).
no code implementations • 21 Jul 2019 • Antonia Saravanou, Clemens Noelke, Nicholas Huntington, Dolores Acevedo-Garcia, Dimitrios Gunopulos
The Infant Mortality Rate (IMR) is the number of infants per 1000 that do not survive until their first birthday.
1 code implementation • COLING 2016 • Nikolaos Panagiotou, Cem Akkaya, Kostas Tsioutsiouliklis, Vana Kalogeraki, Dimitrios Gunopulos
News portals, such as Yahoo News or Google News, collect large amounts of documents from a variety of sources on a daily basis.
no code implementations • 1 Jul 2014 • Dimitrios Kotsakos, Theodoros Lappas, Dimitrios Kotzias, Dimitrios Gunopulos, Nattiya Kanhabua, Kjetil Nørvåg
A large number of mainstream applications, like temporal search, event detection, and trend identification, assume knowledge of the timestamp of every document in a given textual collection.
Ranked #3 on Document Dating on APW