Search Results for author: Pedro Mendes

Found 11 papers, 4 papers with code

Reproducibility and FAIR Principles: The Case of a Segment Polarity Network Model

1 code implementation18 Apr 2023 Pedro Mendes

The issue of reproducibility of computational models and the related FAIR principles (findable, accessible, interoperable, and reusable) are examined in a specific test case.

Hyper-parameter Tuning for Adversarially Robust Models

1 code implementation5 Apr 2023 Pedro Mendes, Paolo Romano, David Garlan

This work focuses on the problem of hyper-parameter tuning (HPT) for robust (i. e., adversarially trained) models, shedding light on the new challenges and opportunities arising during the HPT process for robust models.

Adversarial Robustness

BioSimulators: a central registry of simulation engines and services for recommending specific tools

no code implementations13 Mar 2022 Bilal Shaikh, Lucian P. Smith, Dan Vasilescu, Gnaneswara Marupilla, Michael Wilson, Eran Agmon, Henry Agnew, Steven S. Andrews, Azraf Anwar, Moritz E. Beber, Frank T. Bergmann, David Brooks, Lutz Brusch, Laurence Calzone, Kiri Choi, Joshua Cooper, John Detloff, Brian Drawert, Michel Dumontier, G. Bard Ermentrout, James R. Faeder, Andrew P. Freiburger, Fabian Fröhlich, Akira Funahashi, Alan Garny, John H. Gennari, Padraig Gleeson, Anne Goelzer, Zachary Haiman, Joseph L. Hellerstein, Stefan Hoops, Jon C. Ison, Diego Jahn, Henry V. Jakubowski, Ryann Jordan, Matúš Kalaš, Matthias König, Wolfram Liebermeister, Synchon Mandal, Robert McDougal, J. Kyle Medley, Pedro Mendes, Robert Müller, Chris J. Myers, Aurelien Naldi, Tung V. N. Nguyen, David P. Nickerson, Brett G. Olivier, Drashti Patoliya, Loïc Paulevé, Linda R. Petzold, Ankita Priya, Anand K. Rampadarath, Johann M. Rohwer, Ali S. Saglam, Dilawar Singh, Ankur Sinha, Jacky Snoep, Hugh Sorby, Ryan Spangler, Jörn Starruß, Payton J. Thomas, David van Niekerk, Daniel Weindl, Fengkai Zhang, Anna Zhukova, Arthur P. Goldberg, Michael L. Blinov, Herbert M. Sauro, Ion I. Moraru, Jonathan R. Karr

To help investigators find and use simulation tools, we developed BioSimulators (https://biosimulators. org), a central registry of the capabilities of simulation tools and consistent Python, command-line, and containerized interfaces to each version of each tool.

ShinyCOPASI: a web-based exploratory interface for COPASI models

1 code implementation7 Oct 2021 Abhishekh Gupta, Pedro Mendes

COPASI is a popular application for simulation and analysis of biochemical networks and their dynamics.

HyperJump: Accelerating HyperBand via Risk Modelling

1 code implementation5 Aug 2021 Pedro Mendes, Maria Casimiro, Paolo Romano, David Garlan

In the literature on hyper-parameter tuning, a number of recent solutions rely on low-fidelity observations (e. g., training with sub-sampled datasets) in order to efficiently identify promising configurations to be then tested via high-fidelity observations (e. g., using the full dataset).

TrimTuner: Efficient Optimization of Machine Learning Jobs in the Cloud via Sub-Sampling

no code implementations9 Nov 2020 Pedro Mendes, Maria Casimiro, Paolo Romano, David Garlan

This work introduces TrimTuner, the first system for optimizing machine learning jobs in the cloud to exploit sub-sampling techniques to reduce the cost of the optimization process while keeping into account user-specified constraints.

BIG-bench Machine Learning

Reproducible research using biomodels

no code implementations4 Jun 2018 Pedro Mendes

Like other types of computational research, modeling and simulation of biological processes (biomodels) is still largely communicated without sufficient detail to allow independent reproduction of results.

Facial Expressions Tracking and Recognition: Database Protocols for Systems Validation and Evaluation

no code implementations2 Jun 2015 Catarina Runa Miranda, Pedro Mendes, Pedro Coelho, Xenxo Alvarez, João Freitas, Miguel Sales Dias, Verónica Costa Orvalho

Following this methodology, we also propose two protocols that allow the capturing of facial behaviors under uncontrolled and real-life situations.

Face Recognition

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