publications

Below is a selected list. See full list at google scholar

2025

  1. AML
    Super-Efficient Exact Hamiltonian Monte Carlo for the von Mises Distribution
    Ari Pakman
    Applied Mathematics Letters, 2025

2024

  1. ICML Workshop
    Amortized probabilistic detection of communities in graphs
    Yueqi Wang, Yoonho Lee, Pallab Basu, Juho Lee, Yee Whye Teh, Liam Paninski, and Ari Pakman
    Structured Probabilistic Inference & Generative Modeling workshop of ICML 2024, Vienna, Austria, 2024
  2. ICML Workshop
    von Mises quasi-processes for Bayesian circular regression
    Yarden Cohen, Alexandre Khae Wu Navarro, Jes Frellsen, Richard E Turner, Raziel Riemer, and Ari Pakman
    Structured Probabilistic Inference & Generative Modeling workshop of ICML 2024, Vienna, Austria, 2024

2021

  1. AAS
    A Bayesian nonparametric approach to super-resolution single-molecule localization
    M. Gabitto, H. Marie-Nelly, A. Pakman, A. Pataki, X. Darzacq, and M Jordan
    The Annals of Applied Statistics, 2021
  2. NeurIPS
    Estimating the unique information of continuous variables
    A. Pakman, A. Nejatbakhsh, D. Gilboa, A. Makkeh, L. Mazzucato, M. Wibral, and E. Schneidman
    Advances in Neural Information Processing Systems, 2021

2020

  1. ICML
    Neural clustering processes
    A. Pakman, Y. Wang, C. Mitelut, J. Lee, and L. Paninski
    In International Conference on Machine Learning, 2020
    Code

2017

  1. ICML
    Stochastic bouncy particle sampler
    A. Pakman, D. Gilboa, D. Carlson, and L. Paninski
    In International Conference on Machine Learning, 2017

2016

  1. UAI
    Taming the noise in reinforcement learning via soft updates
    R. Fox*, A. Pakman*, and N. Tishby
    In Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016
  2. ICML
    Partition functions from Rao-Blackwellized tempered sampling
    D. Carlson*, P. Stinson*, A. Pakman*, and Liam Paninski
    In International Conference on Machine Learning, 2016

2013

  1. NeurIPS
    Auxiliary-variable exact Hamiltonian Monte Carlo samplers for binary distributions
    A. Pakman, and L. Paninski
    Advances in neural information processing systems, 2013