Retrieval of Experiments with Sequential Dirichlet Process Mixtures in Model Space. - Ritabrata Dutta; Sohan Seth; Samuel Kaski (CoRR, 2013)

Modelling-based experiment retrieval: a case study with gene expression clustering. - Paul Blomstedt; Ritabrata Dutta; Sohan Seth; Alvis Brazma; Samuel Kaski (Bioinform., 2016)

ABCpy: A User-Friendly, Extensible, and Parallel Library for Approximate Bayesian Computation. - Ritabrata Dutta; Marcel Schöngens; Jukka-Pekka Onnela; Antonietta Mira (PASC, 2017)

Likelihood-free inference via classification. - Michael U. Gutmann; Ritabrata Dutta; Samuel Kaski; Jukka Corander (Stat. Comput., 2018)

Probabilistic Forecasting with Conditional Generative Networks via Scoring Rule Minimization. - Lorenzo Pacchiardi; Rilwan Adewoyin; Peter Dueben; Ritabrata Dutta (CoRR, 2021)

ABCpy: A High-Performance Computing Perspective to Approximate Bayesian Computation. - Ritabrata Dutta; Marcel Schöngens; Lorenzo Pacchiardi; Avinash Ummadisingu; Nicole Widmer; Pierre Künzli; Jukka-Pekka Onnela; Antonietta Mira (J. Stat. Softw., 2021)

TRU-NET: a deep learning approach to high resolution prediction of rainfall. - Rilwan A. Adewoyin; Peter Dueben; Peter Watson; Yulan He 001; Ritabrata Dutta (Mach. Learn., 2021)

Using mobility data in the design of optimal lockdown strategies for the COVID-19 pandemic. - Ritabrata Dutta; Susana N. Gomes; Dante Kalise; Lorenzo Pacchiardi (PLoS Comput. Biol., 2021)

RSTGen: Imbuing Fine-Grained Interpretable Control into Long-FormText Generators. - Rilwan Adewoyin; Ritabrata Dutta; Yulan He 001 (NAACL-HLT, 2022)

Likelihood-Free Inference with Generative Neural Networks via Scoring Rule Minimization. - Lorenzo Pacchiardi; Ritabrata Dutta (CoRR, 2022)

Score Matched Neural Exponential Families for Likelihood-Free Inference. - Lorenzo Pacchiardi; Ritabrata Dutta (J. Mach. Learn. Res., 2022)

Personalized pathology test for Cardio-vascular disease: Approximate Bayesian computation with discriminative summary statistics learning. - Ritabrata Dutta; Karim Zouaoui Boudjeltia; Christos Kotsalos; Alexandre Rousseau; Daniel Ribeiro de Sousa; Jean-Marc Desmet; Alain Van Meerhaeghe; Antonietta Mira; Bastien Chopard (PLoS Comput. Biol., 2022)

Quasi-Bayes meets Vines. - David Huk; Yuanhe Zhang; Ritabrata Dutta; Mark Steel (NeurIPS, 2024)

Generalized Bayesian deep reinforcement learning. - Shreya Sinha Roy; Richard G. Everitt; Christian P. Robert; Ritabrata Dutta (CoRR, 2024)

Estimating Haplotype Structure and Frequencies: A Bayesian Approach to Unknown Design in Pooled Genomic Data. - Yuexuan Wang; Ritabrata Dutta; Andreas Futschik (J. Comput. Biol., 2024)

Probabilistic Forecasting with Generative Networks via Scoring Rule Minimization. - Lorenzo Pacchiardi; Rilwan A. Adewoyin; Peter Dueben; Ritabrata Dutta (J. Mach. Learn. Res., 2024)

Your copula is a classifier in disguise: classification-based copula density estimation. - David Huk; Mark Steel; Ritabrata Dutta (AISTATS, 2025)