activity
20182022
most citedScalable Population Synthesis with Deep Generative Modeling

102 citations · 116 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2022

Large Scale Passenger Detection with Smartphone/Bus Implicit Interaction and Multisensory Unsupervised Cause-effect Learning

Valentino Servizi, Dan R. Persson, Francisco C. Pereira +4

Intelligent Transportation Systems (ITS) underpin the concept of Mobility as a Service (MaaS), which requires universal and seamless users' access across multiple public and privat…

stat.ME2020

Estimating Causal Effects with the Neural Autoregressive Density Estimator

Sergio Garrido, Stanislav S. Borysov, Jeppe Rich +1

Estimation of causal effects is fundamental in situations were the underlying system will be subject to active interventions. Part of building a causal inference engine is defining…

stat.ML2019

Prediction of rare feature combinations in population synthesis: Application of deep generative modelling

Sergio Garrido, Stanislav S. Borysov, Francisco C. Pereira +1

In population synthesis applications, when considering populations with many attributes, a fundamental problem is the estimation of rare combinations of feature attributes. Unsurpr…

stat.ML2019★ 14 cited

Introducing Super Pseudo Panels: Application to Transport Preference Dynamics

Stanislav S. Borysov, Jeppe Rich

We propose a new approach for constructing synthetic pseudo-panel data from cross-sectional data. The pseudo panel and the preferences it intends to describe is constructed at the…

stat.ML2018★ 102 cited

Scalable Population Synthesis with Deep Generative Modeling

Stanislav S. Borysov, Jeppe Rich, Francisco C. Pereira

Population synthesis is concerned with the generation of synthetic yet realistic representations of populations. It is a fundamental problem in the modeling of transport where the…