Adam Goliński

Adam Goliński

Probabilistic Inference, Probablistic Programming

I am a PhD student supervised by Tom Rainforth, Frank Wood and Yee Whye Teh. I am interested in probabilistic programming and inference. So far I have worked mostly on aspects of amortized inference, both for better learning of deep generative models and for speeding up inference on probabilistic programs.

I am part of the AIMS Centre for Doctoral Training.



  • S. Webb , A. Golinski , R. Zinkov , N. Siddharth , T. Rainforth , Y. W. Teh , F. Wood , Faithful Inversion of Generative Models for Effective Amortized Inference, in Advances in Neural Information Processing Systems (NIPS), 2018.
  • A. Golinski , Y. W. Teh , F. Wood , T. Rainforth , Amortized Monte Carlo Integration, UAI 2018 Workshop on Uncertainty in Deep Learning, 2018.