A new stochastic estimator for tremor frequency tracking. - Alp Kucukelbir; Azadeh Kushki; Konstantinos N. Plataniotis (ICASSP, 2009)

Profile Predictive Inference. - Alp Kucukelbir; David M. Blei (CoRR, 2014)

Automatic Variational Inference in Stan. - Alp Kucukelbir; Rajesh Ranganath; Andrew Gelman; David M. Blei (NIPS, 2015)

Population Empirical Bayes. - Alp Kucukelbir; David M. Blei (UAI, 2015)

Variational Inference: A Review for Statisticians. - David M. Blei; Alp Kucukelbir; Jon D. McAuliffe (CoRR, 2016)

Posterior Dispersion Indices. - Alp Kucukelbir; David M. Blei (CoRR, 2016)

Edward: A library for probabilistic modeling, inference, and criticism. - Dustin Tran; Alp Kucukelbir; Adji B. Dieng; Maja Rudolph; Dawen Liang; David M. Blei (CoRR, 2016)

Reweighted Data for Robust Probabilistic Models. - Yixin Wang 002; Alp Kucukelbir; David M. Blei (CoRR, 2016)

Evaluating Bayesian Models with Posterior Dispersion Indices. - Alp Kucukelbir; Yixin Wang 002; David M. Blei (ICML, 2017)

Robust Probabilistic Modeling with Bayesian Data Reweighting. - Yixin Wang 002; Alp Kucukelbir; David M. Blei (ICML, 2017)

Variational Deep Q Network. - Yunhao Tang; Alp Kucukelbir (CoRR, 2017)

Automatic Differentiation Variational Inference. - Alp Kucukelbir; Dustin Tran; Rajesh Ranganath; Andrew Gelman; David M. Blei (J. Mach. Learn. Res., 2017)

Variance Reduction for Evolution Strategies via Structured Control Variates. - Yunhao Tang; Krzysztof Choromanski; Alp Kucukelbir (AISTATS, 2020)

Hindsight Expectation Maximization for Goal-conditioned Reinforcement Learning. - Yunhao Tang; Alp Kucukelbir (AISTATS, 2021)

Treeffuser: probabilistic prediction via conditional diffusions with gradient-boosted trees. - Nicolas Beltran-Velez; Alessandro Antonio Grande; Achille Nazaret; Alp Kucukelbir; David M. Blei (NeurIPS, 2024)

Treeffuser: Probabilistic Predictions via Conditional Diffusions with Gradient-Boosted Trees. - Nicolas Beltran-Velez; Alessandro Antonio Grande; Achille Nazaret; Alp Kucukelbir; David M. Blei (CoRR, 2024)