Babak Shahbaba

Orcid: 0000-0002-8102-1609

Affiliations:
  • University of California, Irvine, USA


According to our database1, Babak Shahbaba authored at least 22 papers between 2006 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

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Bibliography

2023
A Model-Agnostic Graph Neural Network for Integrating Local and Global Information.
CoRR, 2023

Fully Bayesian Autoencoders with Latent Sparse Gaussian Processes.
Proceedings of the International Conference on Machine Learning, 2023

2022
Scaling Up Bayesian Uncertainty Quantification for Inverse Problems Using Deep Neural Networks.
SIAM/ASA J. Uncertain. Quantification, December, 2022

Brain waves analysis via a non-parametric Bayesian mixture of autoregressive kernels.
Comput. Stat. Data Anal., 2022

2020
Conjoined Dirichlet Process.
CoRR, 2020

Nonparametric Fisher Geometry with Application to Density Estimation.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

2019
Neural network gradient Hamiltonian Monte Carlo.
Comput. Stat., 2019

Bayesian Neural Decoding Using A Diversity-Encouraging Latent Representation Learning Method.
CoRR, 2019

Modeling Dynamic Functional Connectivity with Latent Factor Gaussian Processes.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018
Modeling Binary Time Series Using Gaussian Processes with Application to Predicting Sleep States.
J. Classif., 2018

2017
Hamiltonian Monte Carlo acceleration using surrogate functions with random bases.
Stat. Comput., 2017

Precomputing strategy for Hamiltonian Monte Carlo method based on regularity in parameter space.
Comput. Stat., 2017

2016
What time is it? Deep learning approaches for circadian rhythms.
Bioinform., 2016

2015
An efficient Bayesian inference framework for coalescent-based nonparametric phylodynamics.
Bioinform., 2015

2014
Split Hamiltonian Monte Carlo.
Stat. Comput., 2014

A Semiparametric Bayesian Model for Detecting Synchrony Among Multiple Neurons.
Neural Comput., 2014

Spherical Hamiltonian Monte Carlo for Constrained Target Distributions.
Proceedings of the 31th International Conference on Machine Learning, 2014

Distributed Stochastic Gradient MCMC.
Proceedings of the 31th International Conference on Machine Learning, 2014

Wormhole Hamiltonian Monte Carlo.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2009
Nonlinear Models Using Dirichlet Process Mixtures.
J. Mach. Learn. Res., 2009

2008
A modified Dirichlet process mixture model for clustering phosphopeptides based on their response to anti-cancer drug perturbation.
Proceedings of the International Conference on Bioinformatics & Computational Biology, 2008

2006
Gene function classification using Bayesian models with hierarchy-based priors.
BMC Bioinform., 2006


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