Localization: using Particle Filter to localize Autonomous Vehicles (Udacity Self Driving Car Nanodegree)
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May 16, 2017 - C++
Localization: using Particle Filter to localize Autonomous Vehicles (Udacity Self Driving Car Nanodegree)
Implementation of a simple 2D EKF with lidar and radar measurements
SLM is a Bayesian skipgram language model based on hierarchical Pitman-Yor processes. It facilitates multiple backoff strategies, interpolation strategies, and offers tools to train and evaluate language models, and rescore nbest lists
Bayesian Macroeconometrics C++ Library
Code for Scalable Bayesian Variable Selection for Negative Binomial Regression Models. See Miao et al. (2019), in Flexible Bayesian Regression Modelling, Yanan F. et al (Eds), Elsevier, to appear.
Header-only Bayes Filters Library
A Python library for the state-of-the-art Bayesian optimization algorithms, with the core implemented in C++.
Estimate the Deterministic Input, Noisy "And" Gate (DINA) cognitive diagnostic model parameters using the Gibbs sampler described by Culpepper (2015) <doi:10.3102/1076998615595403>.
C++ template library for probabilistic programming
Found this old C++ Bayesian Network program I wrote as part of an AI class back in 2012
An algorithm for bayesian regression with uncertainties in all dimensions.
Bayesian spatial regression with Meshed Gaussian Process
Spline implementation of Spatial Temporal Aggregated Predictors(STAP). Enables the identification and estimation of BEF network effects with both cross-sectional and longitudinal data.
Nested Dirichlet Process Mixture Models to characterize Built Environment Data
Codes for Chandra, et al. (2021+). Escaping the curse of dimensionality in Bayesian model based clustering. Please refer to the original paper for details https://arxiv.org/abs/2006.02700
Supporting data and code for manuscript titled 'Modelling the persistence and control of Rift Valley fever virus in a spatially heterogeneous landscape'.
Time varying vector autoregressive state space modeling of community interactions in a Bayesian framework
Jointly model the accuracy of cognitive responses and item choices within a bayesian hierarchical framework as described by Culpepper and Balamuta (2015) <doi:10.1007/s11336-015-9484-7>. In addition, the package contains the datasets used within the analysis of the paper.
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