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2020 – today
- 2024
[j9]Yuexuan Wang
, Ritabrata Dutta, Andreas Futschik:
Estimating Haplotype Structure and Frequencies: A Bayesian Approach to Unknown Design in Pooled Genomic Data. J. Comput. Biol. 31(8): 708-726 (2024)- [j8]Lorenzo Pacchiardi, Rilwan A. Adewoyin, Peter Dueben, Ritabrata Dutta:
Probabilistic Forecasting with Generative Networks via Scoring Rule Minimization. J. Mach. Learn. Res. 25: 45:1-45:64 (2024) - [i7]David Huk, Yuanhe Zhang, Mark Steel, Ritabrata Dutta:
Quasi-Bayes meets Vines. CoRR abs/2406.12764 (2024) - 2022
- [j7]Lorenzo Pacchiardi, Ritabrata Dutta:
Score Matched Neural Exponential Families for Likelihood-Free Inference. J. Mach. Learn. Res. 23: 38:1-38:71 (2022) - [j6]Ritabrata Dutta, Karim Zouaoui Boudjeltia, Christos Kotsalos, Alexandre Rousseau, Daniel Ribeiro de Sousa, Jean-Marc Desmet, Alain Van Meerhaeghe, Antonietta Mira, Bastien Chopard:
Personalized pathology test for Cardio-vascular disease: Approximate Bayesian computation with discriminative summary statistics learning. PLoS Comput. Biol. 18(3) (2022) - [c2]Rilwan Adewoyin, Ritabrata Dutta, Yulan He:
RSTGen: Imbuing Fine-Grained Interpretable Control into Long-FormText Generators. NAACL-HLT 2022: 1822-1835 - [i6]Rilwan A. Adewoyin, Ritabrata Dutta, Yulan He:
RSTGen: Imbuing Fine-Grained Interpretable Control into Long-FormText Generators. CoRR abs/2205.12590 (2022) - [i5]Lorenzo Pacchiardi, Ritabrata Dutta:
Likelihood-Free Inference with Generative Neural Networks via Scoring Rule Minimization. CoRR abs/2205.15784 (2022) - 2021
- [j5]Ritabrata Dutta, Marcel Schöngens, Lorenzo Pacchiardi, Avinash Ummadisingu, Nicole Widmer, Pierre Künzli, Jukka-Pekka Onnela, Antonietta Mira:
ABCpy: A High-Performance Computing Perspective to Approximate Bayesian Computation. J. Stat. Softw. 100(7) (2021) - [j4]Rilwan A. Adewoyin, Peter Dueben, Peter Watson, Yulan He, Ritabrata Dutta:
TRU-NET: a deep learning approach to high resolution prediction of rainfall. Mach. Learn. 110(8): 2035-2062 (2021) - [j3]Ritabrata Dutta, Susana N. Gomes, Dante Kalise, Lorenzo Pacchiardi:
Using mobility data in the design of optimal lockdown strategies for the COVID-19 pandemic. PLoS Comput. Biol. 17(8) (2021) - [i4]Lorenzo Pacchiardi, Rilwan Adewoyin, Peter Dueben, Ritabrata Dutta:
Probabilistic Forecasting with Conditional Generative Networks via Scoring Rule Minimization. CoRR abs/2112.08217 (2021) - 2020
- [i3]Rilwan Adewoyin, Peter Dueben, Peter Watson, Yulan He, Ritabrata Dutta:
TRU-NET: A Deep Learning Approach to High Resolution Prediction of Rainfall. CoRR abs/2008.09090 (2020)
2010 – 2019
- 2018
- [j2]Michael U. Gutmann, Ritabrata Dutta, Samuel Kaski, Jukka Corander:
Likelihood-free inference via classification. Stat. Comput. 28(2): 411-425 (2018) - 2017
- [c1]Ritabrata Dutta, Marcel Schöngens, Jukka-Pekka Onnela, Antonietta Mira:
ABCpy: A User-Friendly, Extensible, and Parallel Library for Approximate Bayesian Computation. PASC 2017: 8:1-8:9 - 2016
- [j1]Paul Blomstedt, Ritabrata Dutta, Sohan Seth, Alvis Brazma, Samuel Kaski:
Modelling-based experiment retrieval: a case study with gene expression clustering. Bioinform. 32(9): 1388-1394 (2016) - 2015
- [i2]Paul Blomstedt, Ritabrata Dutta, Sohan Seth, Alvis Brazma, Samuel Kaski:
Modelling-based experiment retrieval: A case study with gene expression clustering. CoRR abs/1505.05007 (2015) - 2013
- [i1]Ritabrata Dutta, Sohan Seth, Samuel Kaski:
Retrieval of Experiments with Sequential Dirichlet Process Mixtures in Model Space. CoRR abs/1310.2125 (2013)
Coauthor Index
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