Search Results for author: Robert Zinkov

Found 7 papers, 2 papers with code

Efficient Bayesian Inference for Nested Simulators

no code implementations pproximateinference AABI Symposium 2019 Bradley Gram-Hansen, Christian Schroeder de Witt, Robert Zinkov, Saeid Naderiparizi, Adam Scibior, Andreas Munk, Frank Wood, Mehrdad Ghadiri, Philip Torr, Yee Whye Teh, Atilim Gunes Baydin, Tom Rainforth

We introduce two approaches for conducting efficient Bayesian inference in stochastic simulators containing nested stochastic sub-procedures, i. e., internal procedures for which the density cannot be calculated directly such as rejection sampling loops.

Bayesian Inference

Querying Word Embeddings for Similarity and Relatedness

no code implementations NAACL 2018 Fatemeh Torabi Asr, Robert Zinkov, Michael Jones

Word embeddings obtained from neural network models such as Word2Vec Skipgram have become popular representations of word meaning and have been evaluated on a variety of word similarity and relatedness norming data.

Word Embeddings Word Similarity

Faithful Inversion of Generative Models for Effective Amortized Inference

no code implementations NeurIPS 2018 Stefan Webb, Adam Golinski, Robert Zinkov, N. Siddharth, Tom Rainforth, Yee Whye Teh, Frank Wood

Inference amortization methods share information across multiple posterior-inference problems, allowing each to be carried out more efficiently.

Using Synthetic Data to Train Neural Networks is Model-Based Reasoning

no code implementations2 Mar 2017 Tuan Anh Le, Atilim Gunes Baydin, Robert Zinkov, Frank Wood

We draw a formal connection between using synthetic training data to optimize neural network parameters and approximate, Bayesian, model-based reasoning.

Composing inference algorithms as program transformations

no code implementations6 Mar 2016 Robert Zinkov, Chung-chieh Shan

Probabilistic inference procedures are usually coded painstakingly from scratch, for each target model and each inference algorithm.

Code Generation Probabilistic Programming

Cannot find the paper you are looking for? You can Submit a new open access paper.