Emille E. O. Ishida

According to our database, Emille E. O. Ishida authored at least 20 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Exploring the Universe with SNAD: Anomaly Detection in Astronomy.

Alina A. Volnova, Patrick D. Aleo, Anastasia Lavrukhina, Etienne Russeil, Timofey Semenikhin, Emmanuel Gangler, Emille E. O. Ishida, Matwey V. Kornilov, Vladimir S. Korolev, Konstantin L. Malanchev, Maria V. Pruzhinskaya, Sreevarsha Sreejith

CoRR, 2024

Coniferest: a complete active anomaly detection framework.

Matwey V. Kornilov, Vladimir S. Korolev, Konstantin L. Malanchev, A. D. Lavrukhina, Etienne Russeil, T. A. Semenikhin, Emmanuel Gangler, Emille E. O. Ishida, Maria V. Pruzhinskaya, Alina A. Volnova, Sreevarsha Sreejith

CoRR, 2024

Multi-View Symbolic Regression.

Etienne Russeil, Fabrício Olivetti de França, Konstantin L. Malanchev, Bogdan Burlacu, Emille E. O. Ishida, Marion Leroux, Clément Michelin, Guillaume Moinard, Emmanuel Gangler

CoRR, 2024

Multiview Symbolic Regression.

Etienne Russeil, Fabrício Olivetti de França, Konstantin L. Malanchev, Bogdan Burlacu, Emille E. O. Ishida, Marion Leroux, Clément Michelin, Guillaume Moinard, Emmanuel Gangler

Proceedings of the Genetic and Evolutionary Computation Conference, 2024

2023

A graph-based spectral classification of Type II supernovae.

Rafael S. de Souza, S. Thorp, Lluís Galbany, Emille E. O. Ishida, Santiago Gonzalez-Gaitan, M. A. Schmitz, Alberto Krone-Martins, C. Peters

Astron. Comput., July, 2023

From Images to Features: Unbiased Morphology Classification via Variational Auto-Encoders and Domain Adaptation.

Quanfeng Xu, Shiyin Shen, Rafael S. de Souza, Mi Chen, Renhao Ye, Yumei She, Zhu Chen, Emille E. O. Ishida, Alberto Krone-Martins, Rupesh Durgesh

CoRR, 2023

Sidestepping the inversion of the weak-lensing covariance matrix with Approximate Bayesian Computation.

Martin Kilbinger, Emille E. O. Ishida, Jessi Cisewski-Kehe

Astron. Comput., 2023

2022

Explainable classification of astronomical uncertain time series.

Michael Franklin Mbouopda, Emille E. O. Ishida, Engelbert Mephu Nguifo, Emmanuel Gangler

CoRR, 2022

2021

Fink: early supernovae Ia classification using active learning.

Marco Leoni, Emille E. O. Ishida, Julien Peloton, Anais Möller

CoRR, 2021

The Role of the Human Expert in the Era of Big Data (keynote abstract).

Emille E. O. Ishida

Proceedings of the Supplementary Proceedings of the XXIII International Conference on Data Analytics and Management in Data Intensive Domains, 2021

2020

Active learning with RESSPECT: Resource allocation for extragalactic astronomical transients.

Noble Kennamer, Emille E. O. Ishida, Santiago Gonzalez-Gaitan, Rafael S. de Souza, Alexander Ihler, Kara Ponder, Ricardo Vilalta, Anais Möller, David O. Jones, Mi Dai, Alberto Krone-Martins, Bruno Quint, Sreevarsha Sreejith, Alex I. Malz, Lluís Galbany

Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

2019

Active Anomaly Detection for time-domain discoveries.

Emille E. O. Ishida, Matwey V. Kornilov, Konstantin L. Malanchev, Maria V. Pruzhinskaya, Alina A. Volnova, Vladimir S. Korolev, Florian Mondon, Sreevarsha Sreejith, Anastasia Malancheva, Shubhomoy Das

CoRR, 2019

Machine Learning and the future of Supernova Cosmology.

Emille E. O. Ishida

CoRR, 2019

Use of Machine Learning for Anomaly Detection Problem in Large Astronomical Databases.

Konstantin L. Malanchev, Alina A. Volnova, Matwey V. Kornilov, Maria V. Pruzhinskaya, Emille E. O. Ishida, Florian Mondon, Vladimir S. Korolev

Proceedings of the Selected Papers of the XXI International Conference on Data Analytics and Management in Data Intensive Domains (DAMDID/RCDL 2019), 2019

Realization of Different Techniques for Anomaly Detection in Astronomical Databases.

Konstantin L. Malanchev, Vladimir S. Korolev, Matwey V. Kornilov, Emille E. O. Ishida, Anastasia Malancheva, Florian Mondon, Maria V. Pruzhinskaya, Sreevarsha Sreejith, Alina Volnova

Proceedings of the Data Analytics and Management in Data Intensive Domains, 2019

2017

Photometric redshift estimation: An active learning approach.

Ricardo Vilalta, Emille E. O. Ishida, Róbert Beck, R. Sutrisno, Rafael S. de Souza, Ashish Mahabal

Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

2016

Automated supernova Ia classification using adaptive learning techniques.

Kinjal Dhar Gupta, Renuka Pampana, Ricardo Vilalta, Emille E. O. Ishida, Rafael S. de Souza

Proceedings of the 2016 IEEE Symposium Series on Computational Intelligence, 2016

Exploring the spectroscopic diversity of type Ia supernovae with Deep Learning and Unsupervised Clustering.

Emille E. O. Ishida, Michele Sasdelli, Ricardo Vilalta, Michel Aguena, Vinicius C. Busti, Hugo Camacho, Arlindo M. M. Trindade, Fabian Gieseke, Rafael S. de Souza, Yabebal T. Fantaye, Paolo A. Mazzali

Proceedings of the Astroinformatics 2016, Sorrento, Italy, October 19-25, 2016, 2016

2015

cosmoabc: Likelihood-free inference via Population Monte Carlo Approximate Bayesian Computation.

Emille E. O. Ishida, Sandro D. P. Vitenti, Mariana Penna-Lima, Jessi Cisewski, Rafael S. de Souza, Arlindo M. M. Trindade, Ewan Cameron, Vinicius C. Busti

Astron. Comput., 2015

The overlooked potential of Generalized Linear Models in astronomy-II: Gamma regression and photometric redshifts.

Jonathan Elliott, Rafael S. de Souza, Alberto Krone-Martins, Ewan Cameron, Emille E. O. Ishida, Joseph M. Hilbe

Astron. Comput., 2015