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Emilio Dorigatti
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2020 – today
- 2024
- [i8]Lucas Kook, Chris Kolb, Philipp Schiele, Daniel Dold, Marcel Arpogaus, Cornelius Fritz, Philipp F. M. Baumann, Philipp Kopper, Tobias Pielok, Emilio Dorigatti, David Rügamer:
How Inverse Conditional Flows Can Serve as a Substitute for Distributional Regression. CoRR abs/2405.05429 (2024) - 2023
- [c4]Emilio Dorigatti, Benjamin Schubert, Bernd Bischl, David Rügamer:
Frequentist Uncertainty Quantification in Semi-Structured Neural Networks. AISTATS 2023: 1924-1941 - [c3]Amadeu Scheppach, Hüseyin Anil Gündüz, Emilio Dorigatti, Philipp C. Münch, Alice C. McHardy
, Bernd Bischl, Mina Rezaei, Martin Binder:
Neural Architecture Search for Genomic Sequence Data. CIBCB 2023: 1-10 - [c2]Julian Rodemann, Jann Goschenhofer, Emilio Dorigatti, Thomas Nagler, Thomas Augustin:
Approximately Bayes-optimal pseudo-label selection. UAI 2023: 1762-1773 - [i7]Julian Rodemann, Jann Goschenhofer, Emilio Dorigatti, Thomas Nagler, Thomas Augustin:
Approximate Bayes Optimal Pseudo-Label Selection. CoRR abs/2302.08883 (2023) - 2022
- [c1]Mina Rezaei, Emilio Dorigatti, David Rügamer, Bernd Bischl:
Joint Debiased Representation Learning and Imbalanced Data Clustering. ICDM (Workshops) 2022: 55-62 - [i6]Emilio Dorigatti, Jann Goschenhofer, Benjamin Schubert, Mina Rezaei, Bernd Bischl:
Positive-Unlabeled Learning with Uncertainty-aware Pseudo-label Selection. CoRR abs/2201.13192 (2022) - [i5]Emilio Dorigatti, Jonas Schweisthal, Bernd Bischl, Mina Rezaei:
Robust and Efficient Imbalanced Positive-Unlabeled Learning with Self-supervision. CoRR abs/2209.02459 (2022) - [i4]Shunjie-Fabian Zheng, JaeEun Nam, Emilio Dorigatti, Bernd Bischl, Shekoofeh Azizi, Mina Rezaei:
Joint Debiased Representation and Image Clustering Learning with Self-Supervision. CoRR abs/2209.06941 (2022) - [i3]Emilio Dorigatti, Bernd Bischl, Benjamin Schubert:
Improved proteasomal cleavage prediction with positive-unlabeled learning. CoRR abs/2209.07527 (2022) - 2021
- [i2]Cornelius Fritz, Emilio Dorigatti, David Rügamer:
Combining Graph Neural Networks and Spatio-temporal Disease Models to Predict COVID-19 Cases in Germany. CoRR abs/2101.00661 (2021) - [i1]Mina Rezaei, Emilio Dorigatti, David Rügamer, Bernd Bischl:
Learning Statistical Representation with Joint Deep Embedded Clustering. CoRR abs/2109.05232 (2021) - 2020
- [j2]Emilio Dorigatti
, Benjamin Schubert:
Graph-theoretical formulation of the generalized epitope-based vaccine design problem. PLoS Comput. Biol. 16(10) (2020)
2010 – 2019
- 2018
- [j1]Marco Fossati
, Emilio Dorigatti, Claudio Giuliano
:
N-ary relation extraction for simultaneous T-Box and A-Box knowledge base augmentation. Semantic Web 9(4): 413-439 (2018)
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