Pinned Repositories
amortized-mxl
Amortized-MXL: Scaling Bayesian Inference of Mixed Multinomial Logit Models to Very Large Datasets
CAREL
CAREL is open-source callback-based framework for promoting the flexible evaluation of different deep RL configurations under a traffic simulation environment.
Combining-TimeSeries-TextData
A deep learning approach for combining time-series and textual data for taxi demand prediction in event areas
CrowdLayer
A neural network layer that enables training of deep neural networks directly from crowdsourced labels (e.g. from Amazon Mechanical Turk) or, more generally, labels from multiple annotators with different biases and levels of expertise.
DCM-ARD
A Bayesian ARD approach for automatically determining an optimal utility function specification in Discrete Choice Models (DCMs) from an exponentially large set of possible specifications in a purely data-driven manner.
DeepJMQR
Deep joint mean and quantile regression for spatio-temporal problems
MA-sLDAc
Multi-Annotator Supervised LDA for classification
mobility-baselines
Baselines and benchmarks for spatio-temporal forecasting problems in transportation.
pyDCML
PyDCML is a Python library for fast implementation and scalable inference of Bayesian Discrete Choice Models that makes it easy to leverage flexible state-of-the-art modelling techniques from Machine Learning, while remaining interpretable and preserving the links with economic theories.
texttk
Text Preprocessing in Python
fmpr's Repositories
fmpr/CrowdLayer
A neural network layer that enables training of deep neural networks directly from crowdsourced labels (e.g. from Amazon Mechanical Turk) or, more generally, labels from multiple annotators with different biases and levels of expertise.
fmpr/Combining-TimeSeries-TextData
A deep learning approach for combining time-series and textual data for taxi demand prediction in event areas
fmpr/texttk
Text Preprocessing in Python
fmpr/DeepJMQR
Deep joint mean and quantile regression for spatio-temporal problems
fmpr/CAREL
CAREL is open-source callback-based framework for promoting the flexible evaluation of different deep RL configurations under a traffic simulation environment.
fmpr/mobility-baselines
Baselines and benchmarks for spatio-temporal forecasting problems in transportation.
fmpr/pyDCML
PyDCML is a Python library for fast implementation and scalable inference of Bayesian Discrete Choice Models that makes it easy to leverage flexible state-of-the-art modelling techniques from Machine Learning, while remaining interpretable and preserving the links with economic theories.
fmpr/MA-sLDAc
Multi-Annotator Supervised LDA for classification
fmpr/amortized-mxl
Amortized-MXL: Scaling Bayesian Inference of Mixed Multinomial Logit Models to Very Large Datasets
fmpr/LogReg-Crowds
Logistic Regression from Crowds
fmpr/DCM-ARD
A Bayesian ARD approach for automatically determining an optimal utility function specification in Discrete Choice Models (DCMs) from an exponentially large set of possible specifications in a purely data-driven manner.
fmpr/MA-sLDAr
Multi-Annotator Supervised LDA for regression
fmpr/edward
A library for probabilistic modeling, inference, and criticism. Deep generative models, variational inference. Runs on TensorFlow.