Travelled to:1 × Germany
1 × Russia
1 × USA
1 × Uruguay
2 × Italy
2 × United Kingdom
Collaborated with:A.D.Gordon C.V.Russo T.Graepel I.G.Baltopoulos K.Bhargavan G.Claret S.K.Rajamani A.V.Nori M.Szymczak N.Rolland S.Bhat M.Greenberg J.Margetson J.V.Gael J.Guiver Long Ouyang A.Scibior D.Tarlow S.Huang M.Johansson P.Raabjerg B.Victor J.Å.Pohjola J.Parrow M.Aizatulin
Talks about:probabilist (4) program (4) bayesian (3) function (2) spreadsheet (1) transform (1) broadcast (1) wireless (1) protocol (1) maintain (1)
Person: Johannes Borgström
DBLP: Borgstr=ouml=m:Johannes
Contributed to:
2015
2014
20132013
2013
20112011
2011
20092016Wrote 10 papers:
- ESOP-2015-GordonRSBRGT #probability #query #source code #spreadsheet
- Probabilistic Programs as Spreadsheet Queries (ADG, CVR, MS, JB, NR, TG, DT), pp. 1–25.
- POPL-2014-GordonGRRBG #named #probability #programming language
- Tabular: a schema-driven probabilistic programming language (ADG, TG, NR, CVR, JB, JG), pp. 321–334.
- ESEC-FSE-2013-ClaretRNGB #analysis #data flow #using
- Bayesian inference using data flow analysis (GC, SKR, AVN, ADG, JB), pp. 92–102.
- POPL-2013-GordonABCGNRR #reasoning
- A model-learner pattern for bayesian reasoning (ADG, MA, JB, GC, TG, AVN, SKR, CVR), pp. 403–416.
- TACAS-2013-BhatBGR #functional #probability #source code
- Deriving Probability Density Functions from Probabilistic Functional Programs (SB, JB, ADG, CVR), pp. 508–522.
- ECOOP-2011-BaltopoulosBG #database #maintenance #refinement
- Maintaining Database Integrity with Refinement Types (IGB, JB, ADG), pp. 484–509.
- ESOP-2011-BorgstromGGMG #machine learning #semantics
- Measure Transformer Semantics for Bayesian Machine Learning (JB, ADG, MG, JM, JVG), pp. 77–96.
- SEFM-2011-BorgstromHJRVPP #calculus #protocol
- Broadcast Psi-calculi with an Application to Wireless Protocols (JB, SH, MJ, PR, BV, JÅP, JP), pp. 74–89.
- Haskell-2009-BorgstromBG #composition #haskell
- A compositional theory for STM Haskell (JB, KB, ADG), pp. 69–80.
- POPL-2016-BorgstromGORSS #named #probability #programming
- Fabular: regression formulas as probabilistic programming (JB, ADG, LO, CVR, AS, MS), pp. 271–283.