default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDStatistics and Computing, Volume 33
Volume 33, Number 1, February 2023
- Zheyuan Li
, Jiguo Cao:
Automatic search intervals for the smoothing parameter in penalized splines. 1 - Rico Krueger, Michel Bierlaire, Thomas Gasos, Prateek Bansal:
Robust discrete choice models with t-distributed kernel errors. 2 - Francisco Vargas, Andrius Ovsianas, David Fernandes, Mark Girolami, Neil D. Lawrence, Nikolas Nüsken:
Bayesian learning via neural Schrödinger-Föllmer flows. 3 - Michael Grabchak, Piergiacomo Sabino:
Efficient simulation of p-tempered α-stable OU processes. 4 - Marco Capó, Aritz Pérez, José Antonio Lozano:
LASSO for streaming data with adaptative filtering. 5 - Angelos Alexopoulos, Petros Dellaportas, Michalis K. Titsias:
Variance reduction for Metropolis-Hastings samplers. 6 - Alan R. Vazquez, Weng Kee Wong, Peter Goos:
Constructing two-level QB-optimal screening designs using mixed-integer programming and heuristic algorithms. 7 - Joris Bierkens, Sebastiano Grazzi, Frank van der Meulen, Moritz Schauer:
Sticky PDMP samplers for sparse and local inference problems. 8 - Siyu Yi, Yong-Dao Zhou:
Model-free global likelihood subsampling for massive data. 9 - Nha Vo-Thanh, Hans-Peter Piepho:
Bayesian A-optimal two-phase designs with a single blocking factor in each phase. 10 - Anna L. Smith, Tian Zheng, Andrew Gelman:
Prediction scoring of data-driven discoveries for reproducible research. 11 - Zhirong Yang, Yuwei Chen, Denis Sedov, Samuel Kaski, Jukka Corander:
Stochastic cluster embedding. 12 - Shufei Ge, Shijia Wang, Lloyd T. Elliott:
Shape modeling with spline partitions. 13 - Rou Zhong, Shishi Liu, Haocheng Li, Jingxiao Zhang:
Sparse logistic functional principal component analysis for binary data. 15 - Lukas Cironis, Jan Palczewski, Georgios Aivaliotis:
Automatic model training under restrictive time constraints. 16 - Gabriel Riutort-Mayol, Paul-Christian Bürkner, Michael Riis Andersen, Arno Solin, Aki Vehtari:
Practical Hilbert space approximate Bayesian Gaussian processes for probabilistic programming. 17 - Vojtech Kejzlar, Tapabrata Maiti:
Variational inference with vine copulas: an efficient approach for Bayesian computer model calibration. 18 - Mohamed Maama, Ajay Jasra, Hernando C. Ombao:
Bayesian parameter inference for partially observed stochastic differential equations driven by fractional Brownian motion. 19 - Nikolai Spuck, Matthias Schmid, Nils Heim, Ute Klarmann-Schulz, Achim Hörauf, Moritz Berger:
Flexible tree-structured regression models for discrete event times. 20 - Victor Freguglia, Nancy Lopes Garcia:
Detecting renewal states in chains of variable length via intrinsic Bayes factors. 21 - Andrew M. Raim:
Direct sampling with a step function. 22 - Kamran Pentland, Massimiliano Tamborrino, Timothy John Sullivan, James Buchanan, Lynton C. Appel:
GParareal: a time-parallel ODE solver using Gaussian process emulation. 23 - Lucas Kock, Nadja Klein, David J. Nott:
Correction to : Variational inference and sparsity in high-dimensional deep Gaussian mixture models. 24 - Lisa Gaedke-Merzhäuser, Janet van Niekerk, Olaf Schenk, Håvard Rue:
Parallelized integrated nested Laplace approximations for fast Bayesian inference. 25 - Pekka Korhonen, Francis K. C. Hui, Jenni Niku, Sara Taskinen:
Fast and universal estimation of latent variable models using extended variational approximations. 26 - Yeonjoo Lee, Natalia Rojas-Perilla, Marina Runge, Timo Schmid:
Variable selection using conditional AIC for linear mixed models with data-driven transformations. 27 - Thomas Rusch, Patrick Mair, Kurt Hornik:
Structure-based hyperparameter selection with Bayesian optimization in multidimensional scaling. 28 - Arnaud Poinas, Rémi Bardenet:
On proportional volume sampling for experimental design in general spaces. 29 - Junyi Zhang, Angelos Dassios:
Truncated Poisson-Dirichlet approximation for Dirichlet process hierarchical models. 30 - Hiroshi Yamashita, Hideyuki Suzuki, Kazuyuki Aihara:
Entropic herding. 31 - Katherine A. L. Valeriano, Christian E. Galarza, Larissa A. Matos:
Moments and random number generation for the truncated elliptical family of distributions. 32 - Atlanta Chakraborty, David J. Nott, Christopher C. Drovandi, David T. Frazier, Scott A. Sisson:
Modularized Bayesian analyses and cutting feedback in likelihood-free inference. 33 - Daniel Ahfock, William J. Astle, Sylvia Richardson:
On randomized sketching algorithms and the Tracy-Widom law. 34 - Bradley Wakefield, Yan-Xia Lin, Rathindra Sarathy, Krishnamurty Muralidhar:
Moment-based density estimation of confidential micro-data: a computational statistics approach. 35
Volume 33, Number 2, April 2023
- Belén Pulido, Alba M. Franco Pereira, Rosa E. Lillo:
A fast epigraph and hypograph-based approach for clustering functional data. 36 - David Rügamer, Philipp F. M. Baumann, Thomas Kneib, Torsten Hothorn:
Probabilistic time series forecasts with autoregressive transformation models. 37 - Li-Pang Chen:
De-noising boosting methods for variable selection and estimation subject to error-prone variables. 38 - Shouto Yonekura, Shonosuke Sugasawa:
Adaptation of the tuning parameter in general Bayesian inference with robust divergence. 39 - Eya Ben Amar, Nadhir Ben Rached, Abdul-Lateef Haji-Ali, Raúl Tempone:
State-dependent importance sampling for estimating expectations of functionals of sums of independent random variables. 40 - Clément Duhamel, Céline Helbert, Miguel Munoz Zuniga, Clémentine Prieur, Delphine Sinoquet:
A SUR version of the Bichon criterion for excursion set estimation. 41 - Marko Järvenpää, Jukka Corander:
On predictive inference for intractable models via approximate Bayesian computation. 42 - Huibin Weng, Olivier Parent:
Beyond homophilic dyadic interactions: the impact of network formation on individual outcomes. 43 - Ionut Paun, Dirk Husmeier, Colin J. Torney:
Stochastic variational inference for scalable non-stationary Gaussian process regression. 44 - Zhuang Yang, Li Ma:
Adaptive step size rules for stochastic optimization in large-scale learning. 45 - Gery Geenens, Alicia Nieto-Reyes, Giacomo Francisci:
Statistical depth in abstract metric spaces. 46 - Ensiyeh Nezakati, Eugen Pircalabelu:
Unbalanced distributed estimation and inference for the precision matrix in Gaussian graphical models. 47 - Christopher J. Geoga, Oana Marin, Michel Schanen, Michael L. Stein:
Fitting Matérn smoothness parameters using automatic differentiation. 48 - Mateusz B. Majka, Marc Sabate Vidales, Lukasz Szpruch:
Multi-index antithetic stochastic gradient algorithm. 49 - Iván Gutiérrez, Luis Gutiérrez, Danilo Alvares:
A new flexible Bayesian hypothesis test for multivariate data. 50 - João Victor B. de Freitas, Caio L. N. Azevedo, Juvêncio S. Nobre:
A stochastic approximation ECME algorithm to semi-parametric scale mixtures of centred skew normal regression models. 51 - Al-Fahad M. Al-Qadhi, Carey E. Priebe, Hayden S. Helm, Vince Lyzinski:
Subgraph nomination: query by example subgraph retrieval in networks. 52 - Philipp Sterzinger, Ioannis Kosmidis:
Maximum softly-penalized likelihood for mixed effects logistic regression. 53 - Zaida C. Quiroz, Marcos Oliveira Prates, Dipak K. Dey, Håvard Rue:
Fast Bayesian inference of block Nearest Neighbor Gaussian models for large data. 54 - Edoardo Redivo, Cinzia Viroli, Alessio Farcomeni:
Quantile-distribution functions and their use for classification, with application to naïve Bayes classifiers. 55
Volume 33, Number 3, June 2023
- Myeongjong Kang, Matthias Katzfuss:
Correlation-based sparse inverse Cholesky factorization for fast Gaussian-process inference. 56 - Xiaoxiao Zhou, Xinyuan Song:
Functional concurrent hidden Markov model. 57 - Chiheb Ben Hammouda, Nadhir Ben Rached, Raúl Tempone, Sophia Wiechert:
Learning-based importance sampling via stochastic optimal control for stochastic reaction networks. 58 - Chien-Yu Peng, Yi-Shian Dong, Tsai-Hung Fan:
The first-passage-time moments for the Hougaard process and its Birnbaum-Saunders approximation. 59 - Filippo Antonazzo, Christophe Biernacki, Christine Keribin:
Frugal Gaussian clustering of huge imbalanced datasets through a bin-marginal approach. 60 - Diala Hawat, Guillaume Gautier, Rémi Bardenet, Raphaël Lachièze-Rey:
On estimating the structure factor of a point process, with applications to hyperuniformity. 61 - Xin Liang:
On the optimality of the Oja's algorithm for online PCA. 62 - Håkon Gryvill, Håkon Tjelmeland:
A sparse matrix formulation of model-based ensemble Kalman filter. 63 - Marno Basson, Tobias M. Louw, Theresa R. Smith:
Variational Tobit Gaussian Process Regression. 64 - Gersende Fort, Eric Moulines:
Stochastic variable metric proximal gradient with variance reduction for non-convex composite optimization. 65 - Jeremie Coullon, Leah F. South, Christopher Nemeth:
Efficient and generalizable tuning strategies for stochastic gradient MCMC. 66 - Min Xu, Zhongfeng Qin:
A Bayesian parametrized method for interval-valued regression models. 67 - Maolin Pan, Minggao Gu, Xianyi Wu, Xiaodan Fan:
Globally and symmetrically identified Bayesian multinomial probit model. 68 - Enes Makalic, Daniel F. Schmidt:
Maximum likelihood estimation of the Weibull distribution with reduced bias. 69 - Marc Lambert, Silvère Bonnabel, Francis R. Bach:
The limited-memory recursive variational Gaussian approximation (L-RVGA). 70 - Meadhbh O'Neill, Kevin Burke:
Variable selection using a smooth information criterion for distributional regression models. 71 - Yujia Ding, Qidi Peng, Zhengming Song, Hansen Chen:
Variable selection and regularization via arbitrary rectangle-range generalized elastic net. 72 - Kangning Wang, Shaomin Li:
Distributed statistical optimization for non-randomly stored big data with application to penalized learning. 73 - Yiming Liu, Shaochen Wang, Wang Zhou:
General Jackknife empirical likelihood and its applications. 74
Volume 33, Number 4, August 2023
- Il-Suk Kang, Hosik Choi, Young Joo Yoon, Junyoung Park, Soon-Sun Kwon, Cheolwoo Park:
Fréchet distance-based cluster analysis for multi-dimensional functional data. 75 - Vaidehi Dixit, Ryan Martin:
A PRticle filter algorithm for nonparametric estimation of multivariate mixing distributions. 76 - Alessandro Mastrototaro, Jimmy Olsson:
Adaptive online variance estimation in particle filters: the ALVar estimator. 77 - Chen Huang, Jieli Ding, Yanqin Feng:
A quadratic upper bound algorithm for regression analysis of credit risk under the proportional hazards model with case-cohort data. 78 - Xiaodong Yang, Jun S. Liu:
Convergence rate of multiple-try Metropolis independent sampler. 79 - Ben Bettisworth, Alexander I. Jordan, Alexandros Stamatakis:
Phylourny: efficiently calculating elimination tournament win probabilities via phylogenetic methods. 80 - Pete Philipson, Alan Huang:
A fast look-up method for Bayesian mean-parameterised Conway-Maxwell-Poisson regression models. 81 - Imke Botha, Robert Kohn, Leah F. South, Christopher C. Drovandi:
Automatically adapting the number of state particles in SMC2. 82 - Tianfang Zhang, Rasmus Bokrantz, Jimmy Olsson:
A similarity-based Bayesian mixture-of-experts model. 83 - Paul G. Beckman, Christopher J. Geoga, Michael L. Stein, Mihai Anitescu:
Scalable computations for nonstationary Gaussian processes. 84 - Armin Eftekhari, Luis Vargas, Konstantinos C. Zygalakis:
The forward-backward envelope for sampling with the overdamped Langevin algorithm. 85 - Haixiang Zhang, Xin Li:
A framework for mediation analysis with massive data. 86 - Efstratios Palias, Ata Kabán:
The effect of intrinsic dimension on the Bayes-error of projected quadratic discriminant classification. 87 - Zishu Zhan, Xiangjie Li, Jingxiao Zhang:
Partial replacement imputation estimation for partially linear models with complex missing pattern covariates. 88 - Shiwei Lan, Shuyi Li, Mirjeta Pasha:
Bayesian spatiotemporal modeling for inverse problems. 89 - Sijing Li, Cheng Zhang, Zhiwen Zhang, Hongkai Zhao:
A data-driven and model-based accelerated Hamiltonian Monte Carlo method for Bayesian elliptic inverse problems. 90 - Anna Bonnet, Miguel Martinez Herrera, Maxime Sangnier:
Inference of multivariate exponential Hawkes processes with inhibition and application to neuronal activity. 91
Volume 33, Number 5, October 2023
- Walter R. Gilks, Lukas Cironis, Stuart Barber:
Wavelet Monte Carlo: a principle for sampling from complex distributions. 92 - Robin Richter, Shankar Bhamidi, Sach Mukherjee:
Improved baselines for causal structure learning on interventional data. 93 - Andreas Anastasiou, Angelos Papanastasiou:
Generalized multiple change-point detection in the structure of multivariate, possibly high-dimensional, data sequences. 94 - Rémi Boutin, Charles Bouveyron, Pierre Latouche:
Embedded topics in the stochastic block model. 95 - Ruiqi Liu, Ganggang Xu, Zuofeng Shang:
Distributed adaptive nearest neighbor classifier: algorithm and theory. 96 - Xinzhu Liang, Shangda Yang, Simon L. Cotter, Kody J. H. Law:
A randomized multi-index sequential Monte Carlo method. 97 - Marta Crispino, Cristina Mollica, Valerio Astuti, Luca Tardella:
Efficient and accurate inference for mixtures of Mallows models with Spearman distance. 98 - Maicon J. Karling, Marc G. Genton, Simos G. Meintanis:
Goodness-of-fit tests for multivariate skewed distributions based on the characteristic function. 99 - Jessica E. Forsyth, Ali H. Al-Anbaki, Berenika Plusa, Simon L. Cotter:
Unlabelled landmark matching via Bayesian data selection, and application to cell matching across imaging modalities. 100 - Xinmin Li, Haozhe Liang, Wolfgang K. Härdle, Hua Liang:
Use generalized linear models or generalized partially linear models? 101 - Yanxin Li, Antonio Linero, Stephen G. Walker:
Latent uniform samplers on multivariate binary spaces. 102 - Julien Demange-Chryst, François Bachoc, Jérôme Morio:
Efficient estimation of multiple expectations with the same sample by adaptive importance sampling and control variates. 103 - Gonzalo Vicente, Aritz Adin, Tomás Goicoa, María Dolores Ugarte:
High-dimensional order-free multivariate spatial disease mapping. 104 - Jason Hou-Liu, Ryan P. Browne:
Generalized linear models for massive data via doubly-sketching. 105 - Michail Tsagris, Abdulaziz Alenazi, Connie Stewart:
Flexible non-parametric regression models for compositional response data with zeros. 106 - Eduardo García-Portugués, Arturo Prieto-Tirado:
Toroidal PCA via density ridges. 107 - Henry A. Palasciano, Guy P. Nason:
A test for the absence of aliasing or white noise in two-dimensional locally stationary wavelet processes. 108 - Tomás Mrkvicka, Mari Myllymäki:
False discovery rate envelopes. 109 - Dean A. Bodenham, Yoshinobu Kawahara:
euMMD: efficiently computing the MMD two-sample test statistic for univariate data. 110 - Mary Llewellyn, Ruth King, Víctor Elvira, Gordon Ross:
A point mass proposal method for Bayesian state-space model fitting. 111 - Samuel I. Watson, Yi Pan:
Evaluation of combinatorial optimisation algorithms for c-optimal experimental designs with correlated observations. 112 - Yan Li, Na Han, Yuxiang Qin, Jing Zhang, Jinxia Su:
Trans-cGAN: transformer-Unet-based generative adversarial networks for cross-modality magnetic resonance image synthesis. 113 - Yao Shi, Wanchunzi Yu, John Stufken:
Optimal designs for generalized linear mixed models based on the penalized quasi-likelihood method. 114 - Danilo Alvares, Valeria Leiva-Yamaguchi:
A two-stage approach for Bayesian joint models: reducing complexity while maintaining accuracy. 115 - Ibrahim Merad, Stéphane Gaïffas:
Robust supervised learning with coordinate gradient descent. 116 - Jiahui Zou, Chaoxia Yuan, Xinyu Zhang, Guohua Zou, Alan T. K. Wan:
Model averaging for support vector classifier by cross-validation. 117 - Sidi Wu, Cédric Beaulac, Jiguo Cao:
Neural networks for scalar input and functional output. 118 - Theodore Papamarkou:
Approximate blocked Gibbs sampling for Bayesian neural networks. 119 - Frédéric Lavancier, Ege Rubak:
On simulation of continuous determinantal point processes. 120
Volume 33, Number 6, December 2023
- Junhan Fang, Grace Y. Yi:
Bayesian analysis for matrix-variate logistic regression with/without response misclassification. 121 - Nicola Pronello, Rosaria Ignaccolo, Luigi Ippoliti, Sara Fontanella:
Penalized model-based clustering of complex functional data. 122 - Salvatore D. Tomarchio, Antonio Punzo, Luca Bagnato:
Parsimonious mixtures for the analysis of tensor-variate data. 123 - Wai Meng Kwok, George Streftaris, Sarat C. Dass:
Laplace based Bayesian inference for ordinary differential equation models using regularized artificial neural networks. 124 - Yuen Tsz Abby Lau, Tianying Wang, Jun Yan, Xuebin Zhang:
Extreme value modeling with errors-in-variables in detection and attribution of changes in climate extremes. 125 - Alessandro Viani, Adam M. Johansen, Alberto Sorrentino:
Cost free hyper-parameter selection/averaging for Bayesian inverse problems with vanilla and Rao-Blackwellized SMC samplers. 126 - Masud Rana, Justin Kosar, Shaqil Peermohamed:
Bayesian hierarchical models incorporating measurement error for interrupted time series design. 127 - Guanjie Lyu, Mohamed Belalia:
Testing symmetry for bivariate copulas using Bernstein polynomials. 128 - Abraão David Costa do Nascimento, Jodavid de A. Ferreira, Alejandro C. Frery:
Unsupervised segmentation of PolSAR data with complex Wishart and ${\varvec{\mathcal {G}}}^{\varvec{0}}_{\varvec{m}}$ distributions and Shannon entropy. 129 - Aniruddha Rajendra Rao, Matthew Reimherr:
Modern non-linear function-on-function regression. 130 - Sigeng Chen, Jeffrey S. Rosenthal, Aki Dote, Hirotaka Tamura, Ali Sheikholeslami:
Optimization via Rejection-Free Partial Neighbor Search. 131 - Lucio Barabesi, Andrea Cerioli, Luis Angel García-Escudero, Agustín Mayo-Íscar:
Consistency factor for the MCD estimator at the Student-t distribution. 132 - Daniela De Canditiis:
Learning binary undirected graph in low dimensional regime. 133 - Andrew Golightly, Laura E. Wadkin, Sam A. Whitaker, Andrew W. Baggaley, Nick G. Parker, Theodore Kypraios:
Accelerating Bayesian inference for stochastic epidemic models using incidence data. 134 - Anja Rappl, Thomas Kneib, Stefan Lang, Elisabeth Bergherr:
Spatial joint models through Bayesian structured piecewise additive joint modelling for longitudinal and time-to-event data. 135 - The Tien Mai:
A reduced-rank approach to predicting multiple binary responses through machine learning. 136 - Timo Schorlepp, Shanyin Tong, Tobias Grafke, Georg Stadler:
Scalable methods for computing sharp extreme event probabilities in infinite-dimensional stochastic systems. 137 - Alexandre Brouste, Christophe Dutang, Lilit Hovsepyan, Tom Rohmer:
One-step closed-form estimator for generalized linear model with categorical explanatory variables. 138 - Lucas Journel, Pierre Monmarché:
Switched diffusion processes for non-convex optimization and saddle points search. 139 - Danli Xu, Yong Wang:
Density estimation for toroidal data using semiparametric mixtures. 140 - Yan Chen, Ruipeng Dong, Canhong Wen:
Communication-efficient estimation for distributed subset selection. 141 - Yan Sun, Shihao Yang:
Manifold-constrained Gaussian process inference for time-varying parameters in dynamic systems. 142
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
last updated on 2025-02-20 19:42 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
