The R2 Project

R2 is a research project within the Programming Languages and Tools group at Microsoft Research India on probabilistic programming. Our goal is to build a user friendly and scalable probabilistic programming system by employing powerful techniques from language design, program analysis and verification.

People
Aditya Nori
Aditya Nori

Sriram Rajamani
Sriram Rajamani

Selva Samuel
Selva Samuel

Deepak Vijaykeerthy
Deepak Vijaykeerthy

Collaborators

  • Johannes Borgström (Uppsala University)
  • Andy Gordon (MSR Cambridge)
  • Chung-Kil Hur (MSR Cambridge)
  • Akash Lal (MSR India)

Interns

  • Arun Chaganty (Stanford University)
  • Guillaume Claret (ENS, Paris)
  • Christian von Essen (Verimag)
  • Vijay D'Silva (UC Berkeley)
  • Selva Samuel (Anna University)
  • Robert J. Simmons (CMU)

Publications

  • Aditya V. Nori, Chung-Kil Hur, Sriram K. Rajamani, and Selva Samuel. R2: An Efficient MCMC Sampler for Probabilistic Programs, In AAAI '14: AAAI Conference on Artificial Intelligence, July 2014
  • Chung-Kil Hur, Aditya V. Nori, Sriram K. Rajamani, and Selva Samuel. Slicing Probabilistic Programs, In PLDI '14: Programming Language Design and Implementation, June 2014
  • Andrew D. Gordon, Thomas A. Henzinger, Aditya V. Nori, and Sriram K. Rajamani. Probabilistic Programming. In ICSE '14: International Conference on Software Engineering (FOSE track), May 2014
  • Aditya V. Nori, Chung-Kil Hur, Sriram K. Rajamani, and Selva Samuel. Semantics Sensitive Sampling for Probabilistic Programs. Microsoft Research Technical Report, MSR-TR-2013-109, October 2013
  • Guillaume Claret, Sriram K. Rajamani, Aditya V. Nori, Andrew D. Gordon, and Johannes Borgström. Bayesian Inference Using Data Flow Analysis. In ESEC-FSE '13: Foundations of Software Engineering, August 2013
  • Arun T. Chaganty, Akash Lal, Aditya V. Nori, and Sriram K. Rajamani. Combining Relational Learning with SMT Solvers using CEGAR. In CAV '13: Computer Aided Verification, July 2013
  • Arun T. Chaganty, Aditya V. Nori, and Sriram K. Rajamani. Efficiently Sampling Probabilistic Programs via Program Analysis. In AISTATS '13: Artificial Intelligence and Statistics, April 2013
  • Andrew D. Gordon, Aditya V. Nori, and Sriram K. Rajamani. Probabilistic Inference using Program Analysis. In OBT '13: Off the Beaten Track Workshop, January 2013
  • Andrew D. Gordon, Mihhail Aizatulin, Johannes Borgström, Guillaume Claret, Thore Graepel, Aditya V. Nori, Sriram K. Rajamani, and Claudio Russo. A Model-Learner Pattern for Bayesian Reasoning. In POPL '13: Principles of Programming Languages, January 2013
  • Arun T. Chaganty, Aditya V. Nori, and Sriram K. Rajamani. Efficiently Sampling Probabilistic Programs via Program Analysis. In NIPS workshop on Probabilistic Programming, December 2012
  • Andrew D. Gordon, Mihhail Aizatulin, Johannes Borgström, Guillaume Claret, Thore Graepel, Aditya V. Nori, Sriram K. Rajamani, and Claudio Russo. A Model-Learner Pattern for Bayesian Reasoning. In NIPS workshop on Probabilistic Programming, December 2012