IMPORTANT WARNING: Phishing! Note that ill-intentioned people may be trying to contact some of participants by email or phone to get money and personal details, by pretending to be part of the staff of our conference center (CIRM). CIRM and the organizers will NEVER contact you by phone on this issue and will NEVER ask you to pay for accommodation/ board / possible registration fee in advance. Any due payment will be taken onsite at CIRM during your stay.
Bayesian methods are now firmly established in the fields of Statistics and Machine Learning and are being increasingly applied to “Big Data”. However, there are still gaps in knowledge about the theory, methodology, computation and application of Bayesian methods in this context.
This conference will bring together an international and interdisciplinary group of researchers and practitioners to share insights, research, challenges and opportunities in developing and using Bayesian statistics in the Big Data era. The anticipated outcomes include: knowledge transfer, new collaborative networks, new research directions and new statistical tools to address challenging problems in the real world.
The program will include oral presentations and substantial time for discussion after each presentation, as well as poster presentations with specific sessions for presentation and discussion.
The program will also include dedicated time for research discussion, collaboration and networking. Sessions on topics such as career pathways and mentoring will be scheduled for postgraduates and early career researchers.
- Pierre Alquier (ENSAE ParisTech)
- Louis Aslett (Durham University)
- Tamara Broderick (MIT)
- Noel Cressie (University of Wollongong): Bayesian Inference for Spatio-Temporal Changes of Arctic Sea Ice
- Marco Cuturi (ENSAE, Paris)
- David B. Dunson (Duke University)
- Gregor Kastner (WU Vienna)
- Ruth King (University of Edinburgh)
- Gary Koop (University of Strathclyde, Glasgow): Composite Likelihood Methods for Large Bayesian VARs with Stochastic Volatility
- Antonio Lijoi (Bocconi University)
- Jean-Michel Marin (Université de Montpellier)
- Antonietta Mira (Università della Svizzera italiana)
- Igor Prünster (Bocconi University)
- Stéphane Robin (AgroParisTech): Shortened Bridge Sampler: Using Deterministic Approximations to Accelerate SMC for Posterior Sampling
- Heejung Shim (University of Melbourne)
- Rebecca Steorts (Duke University)
- Minh-Ngoc Tran (University of Sydney): Bayesian Computation for Big Models Big Data
- Darren Wilkinson (Newcastle University): A Compositional Approach to Scalable Bayesian Computation and Probabilistic Programming
- Atanu Bhattacharjee (Tata Memorial Centre) Time-Course Data Prediction for Repeatedly Measured Gene Expression
- Marta Crispino (INRIA Grenoble)
- Christel Faes (Hasselt University Belgium)
- Ethan Goan (Queensland University of Technology)
- Logan Graham (University of Oxford): Causality in Bayesian Modelling for Modern Machine Learning Challenges
- Clara Grazian (University of Oxford)
- Zitong Li (University of Melbourne)
- Benoit Liquet (Université de Pau et des Pays de L'Adour)
- Jia Liu (University of Helsinki)
- Reza Mohammadi (University of Amsterdam)
- Ahihiko Nishimura (University of California - Los Angeles)
- Monica Patriche (University of Bucharest)
- Gajendra Vishwakarma (Indian Institute of Technology Dhanbad)