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Department of Statistics

Publications

Computational/Methodological Statistics:

  1. Pacchiardi, L., Dutta, R. (2022),"Likelihood-Free Inference with Generative Neural Networks via Scoring Rule Minimization", Preprint.
  2. Pacchiardi, L., Adewoyin, R., Dueben, P., Dutta, R. (2022), "Probabilistic Forecasting with Conditional Generative Networks via Scoring Rule Minimization", Preprint.
  3. Pacchiardi, L., Khoo, S., Dutta, R. (2022), “Generalized Bayesian Likelihood-Free Inference", Preprint [Code]
  4. Lorenzo Pacchiardi, Ritabrata Dutta, (2022), “Score Matched Conditional Exponential Families for Likelihood-Free Inference”, Journal of Machine Learning Research, [Code|Talk].
  5. Owen Thomas, Ritabrata Dutta, Jukka Corander, Samuel Kaski and Michael U. Gutmann, (2021) “Likelihood-free inference by ratio estimation”, Bayesian Analysis
  6. Michael U Gutmann, Ritabrata Dutta, Samuel Kaski, Jukka Corander, (2017), “Likelihood-free inference via classification”, Statistics and Computing
  7. Jaarno Lintusaari, Michael U. Gutmann, Ritabrata Dutta, Samuel Kaski and Jukka Corander, (2016), “Fundamentals and Recent Developments in Approximate Bayesian Computation”, Systematic Biology
  8. Ritabrata Dutta, Jayanta K Ghosh, (2013), “Bayes Model Selection with Path Sampling: Factor Models and Other Examples”, Statistical Science
  9. Ritabrata Dutta, Malgortaza Bogdan, Jayanta K Ghosh, (2012), “Model Selection and Multiple Testing - A Bayesian and Empirical Bayes Overview and some New Results”, Journal of Indian Statistical Association

Statistical Softwares:

  1. Ritabrata Dutta, Marcel Schoengens, Lorenzo Pacchiardi, Avinash Ummadisinghu, Nicole Widmer, Pierre Kunzli, Jukka-Pekka Onnela, Antonietta Mira, (2021), “ABCpy: A High-Performance Computing Perspective to Approximate Bayesian Computation”, Journal of Statistical Software [Code|Documentation|Talk]
  2. Ritabrata Dutta, Marcel Schoengens, Jukka-Pekka Onnela, and Antonietta Mira, (2017) “ABCpy: A User-Friendly, Extensible, and Parallel Library for Approximate Bayesian Computation”, In Proceedings of PASC ’17, Lugano, ACM

Applied Statistics:

Meteorology and Climate science

  1. Lo, S., Watson, P., Dueben, P., Dutta, R., “High-resolution Probabilistic Precipitation Prediction for use in Climate Simulations”, Preprint [Code|Talk]
  2. Adewoyin, R., Dueben, P., Watson, P., He, Y., Dutta, R., (2021) “TRU-NET: A Deep Learning Approach to High Resolution Prediction of Rainfall”, Machine Learning [Code].

Population Genetics

  1. Xu, Y., Futschik, A., Dutta, R. (2022), "Joint likelihood-free inference on the number of selected SNPs and the selection coefficient in an evolving population", Preprint
  2. Wang, Y., Futschik, A., Dutta, R. (2022), "Bayesian linear models with unknown design over finite alphabets", Preprint

Epidemiology

  1. Ritabrata Dutta, Susana Gomes, Dante Kalise, Lorenzo Pacchiardi, (2021) “Using mobility data in the design of optimal lockdown strategies for the COVID-19 pandemic”, PLOS Computational Biology [Code|Talk|Website|Press coverage]
  2. Ritabrata Dutta, Antonietta Mira, Jukka-Pekka Onnela, (2018) “Bayesian Inference of Spreading Processes on Networks”, Proceedings of Royal Society A [Code]

Computational Biology

  1. Cavallaro, M., Wang, Y., Hebenstreit, D., Dutta, R., "Bayesian inference of PolII dynamics over the exclusion process", Royal Society Open Science
  2. Christos Kotsalos, Franck Raynaud, Jonas Latt, Ritabrata Dutta, Frank Dubois, Karim Zouaoui Boudjeltia and Bastien Chopard, (2022), "Shear induced diffusion of platelets revisited", Frontiers in Physiology
  3. Dutta, R., Zouaoui Boudjeltia, K., Kotsalos, C., Rousseau, A., Ribeiro de Sousa, D., Desmet, J., Van Meerhaeghe, A., Mira, A., Chopard, B., (2022), “Personalized pathology test for Cardio-vascular disease: Approximate Bayesian computation with discriminative summary statistics learning”, PLOS Computational Biology, [Code]
  4. Joseph Watson, Robin Boyd, Ritabrata Dutta, Giorgos Vasdekis, Nicola Walker, Shovonlal Roy, Richard Everitt, Kieran Hyder, Richard Sibly, (2022), "Incorporating environmental variability in a spatially-explicit individual-based model of European sea bass.", Ecological Modelling [Code].
  5. Ritabrata Dutta, Bastien Chopard, Jonas Lätt, Frank Dubois, Karim Zouaoui Boudjeltia, Antonietta Mira, (2018), “Parameter estimation of platelets deposition: Approximate Bayesian computation with high performance computing”, Frontiers in Physiology [Code]
  6. Paul Blomstedt, Ritabrata Dutta, Sohan Seth, Alvis Brazma, Samuel Kaski, (2016), “Modelling-based experiment retrieval: A case study with gene expression clustering”, Bioinformatics
  7. Ritabrata Dutta and Ritaban Dutta, (2006), “Maximum Probability Rule” based unsupervised classification of MRSA infections in hospital environment: using Electronic Nose”, Sensors and Actuators B: Chemical
  8. Ritaban Dutta and Ritabrata Dutta, (2006), “Intelligent Bayes Classifier (IBC) for ENT infection classification in hospital environment”, Biomedical Engineering Online

Physical Science and Engineering

  1. Rilwan A. Adewoyin, Ritabrata Dutta, Yulan He, (2022) "RSTGen: Imbuing Fine-Grained Interpretable Control into Long-Form Text Generators", In the proceedings of NAACL2022
  2. Anthony Ebert, Ritabrata Dutta, Paul Wu, Kerrie Mengersen, Fabrizio Ruggeri, Antonietta Mira, (2021) “Likelihood-Free Parameter Estimation for Dynamics Queueing Networks”, Journal of Royal Statistical Society - C
  3. Lorenzo Pacchiardi, Pierre Kunzli, Macrel Schoengens, Bastien Chopard, Ritabrata Dutta, (2020) “Distance-learning For Approximate Bayesian Computation To Model a Volcanic Eruption“, Sankhya-B [Code]
  4. Ritabrata Dutta, Zacharias Faidon Brotzakis, Antonietta Mira, (2018) “Bayesian Calibration of Force-fields from Experimental Data: TIP4P Water”, Journal of Chemical Physics [Code]
  5. Ritabrata Dutta, Arnab Atta and Tapas Kumar Dutta, (2008), “Experimental and Numerical Study of Heat Transfer in Horizontal Concentric Annulus Containing Phase Change Material”, The Canadian Journal of Chemical Engineering

Doctoral Thesis

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