Travelled to:1 × France
Collaborated with:Feras A. Saad Marco F. Cusumano-Towner Alexander K. Lew M.C.Rinard Ulrich Schaechtle J.H.Huggins K.Narasimhan A.Saeedi C.E.Freer Marco Cusumano-Towner B.Bichsel T.Gehr M.T.Vechev Benjamin Sherman M.Carbin Shivam Handa Alexey Radul Y.Chen M.Rinard
Talks about:probabilist (5) program (4) infer (4) programm (3) jump (2) increment (1) distribut (1) synthesi (1) bayesian (1) asymptot (1)
Person: Vikash K. Mansinghka
DBLP: Mansinghka:Vikash_K=
Contributed to:
2015
20182019
20192020Wrote 7 papers:
- ICML-2015-HugginsNSM #markov #named #process
- JUMP-Means: Small-Variance Asymptotics for Markov Jump Processes (JHH, KN, AS, VKM), pp. 693–701.
- PLDI-2018-Cusumano-Towner18a #incremental #probability #source code
- Incremental inference for probabilistic programs (MCT, BB, TG, MTV, VKM), pp. 571–585.
- PLDI-2018-MansinghkaSHRCR #probability #programmable #programming
- Probabilistic programming with programmable inference (VKM, US, SH, AR, YC, MR), pp. 603–616.
- PLDI-2019-Cusumano-Towner #named #probability #programmable #programming
- Gen: a general-purpose probabilistic programming system with programmable inference (MFCT, FAS, AKL, VKM), pp. 221–236.
- POPL-2019-SaadCSRM #automation #modelling #probability #source code #synthesis
- Bayesian synthesis of probabilistic programs for automatic data modeling (FAS, MFCT, US, MCR, VKM), p. 32.
- POPL-2020-LewCSCM #probability #programmable #semantics
- Trace types and denotational semantics for sound programmable inference in probabilistic languages (AKL, MFCT, BS, MC, VKM), p. 32.
- POPL-2020-SaadFRM #approximate #probability
- Optimal approximate sampling from discrete probability distributions (FAS, CEF, MCR, VKM), p. 31.