{"list":"other","total":60,"rows":[{"id":"1412.6980","title":"Adam: A Method for Stochastic Optimization","created":"2014-12-22","cited_by_count":37240},{"id":"1608.03983","title":"SGDR: Stochastic Gradient Descent with Warm Restarts","created":"2016-08-13","cited_by_count":5045},{"id":"1502.01852","title":"Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification","created":"2015-02-06","cited_by_count":3611},{"id":"1601.00670","title":"Variational Inference: A Review for Statisticians","created":"2016-01-04","cited_by_count":1472},{"id":"1703.06114","title":"Deep Sets","created":"2017-03-10","cited_by_count":1421},{"id":"1705.07057","title":"Masked Autoregressive Flow for Density Estimation","created":"2017-05-19","cited_by_count":684},{"id":"1906.04032","title":"Neural Spline Flows","created":"2019-06-10","cited_by_count":596},{"id":"1911.01429","title":"The frontier of simulation-based inference","created":"2019-11-04","cited_by_count":502},{"id":"1808.04730","title":"Analyzing Inverse Problems with Invertible Neural Networks","created":"2018-08-14","cited_by_count":242},{"id":"1905.07488","title":"Automatic Posterior Transformation for Likelihood-Free Inference","created":"2019-05-17","cited_by_count":219},{"id":"1701.02434","title":"A Conceptual Introduction to Hamiltonian Monte Carlo","created":"2017-01-10","cited_by_count":209},{"id":"2101.04653","title":"Benchmarking Simulation-Based Inference","created":"2021-01-12","cited_by_count":162},{"id":"1907.02392","title":"Guided Image Generation with Conditional Invertible Neural Networks","created":"2019-07-04","cited_by_count":147},{"id":"2003.06281","title":"BayesFlow: Learning complex stochastic models with invertible neural networks","created":"2020-03-13","cited_by_count":144},{"id":"1804.06788","title":"Validating Bayesian Inference Algorithms with Simulation-Based Calibration","created":"2018-04-18","cited_by_count":124},{"id":"1507.04544","title":"Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC","created":"2015-07-16","cited_by_count":110},{"id":"2305.17161","title":"Flow Matching for Scalable Simulation-Based Inference","created":"2023-05-26","cited_by_count":101},{"id":"1903.08008","title":"Rank-normalization, folding, and localization: An improved $\\widehat{R}$ for assessing convergence of MCMC","created":"2019-03-19","cited_by_count":93},{"id":"2001.04872","title":"Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)","created":"2020-01-14","cited_by_count":92},{"id":"1903.03704","title":"NeuTra-lizing Bad Geometry in Hamiltonian Monte Carlo Using Neural Transport","created":"2019-03-09","cited_by_count":74},{"id":"2010.10079","title":"Neural Approximate Sufficient Statistics for Implicit Models","created":"2020-10-20","cited_by_count":74},{"id":"2404.09636","title":"All-in-one simulation-based inference","created":"2024-04-15","cited_by_count":74},{"id":"2112.03235","title":"Simulation Intelligence: Towards a New Generation of Scientific Methods","created":"2021-12-06","cited_by_count":68},{"id":"1805.12244","title":"Mining gold from implicit models to improve likelihood-free inference","created":"2018-05-30","cited_by_count":60},{"id":"1802.02538","title":"Yes, but Did It Work?: Evaluating Variational Inference","created":"2018-02-07","cited_by_count":53},{"id":"2210.04872","title":"Sequential Neural Score Estimation: Likelihood-Free Inference with Conditional Score Based Diffusion Models","created":"2022-10-10","cited_by_count":50},{"id":"2011.01808","title":"Bayesian Workflow","created":"2020-11-03","cited_by_count":49},{"id":"2112.08866","title":"Detecting Model Misspecification in Amortized Bayesian Inference with Neural Networks","created":"2021-12-16","cited_by_count":49},{"id":"2209.14249","title":"Compositional Score Modeling for Simulation-based Inference","created":"2022-09-28","cited_by_count":48},{"id":"2305.15871","title":"Learning Robust Statistics for Simulation-based Inference under Model Misspecification","created":"2023-05-25","cited_by_count":48},{"id":"1707.01694","title":"Sparsity information and regularization in the horseshoe and other shrinkage priors","created":"2017-07-06","cited_by_count":43},{"id":"1507.02646","title":"Pareto Smoothed Importance Sampling","created":"2015-07-09","cited_by_count":42},{"id":"2302.09125","title":"JANA: Jointly Amortized Neural Approximation of Complex Bayesian Models","created":"2023-02-17","cited_by_count":41},{"id":"1610.09900","title":"Inference Compilation and Universal Probabilistic Programming","created":"2016-10-31","cited_by_count":32},{"id":"2306.16015","title":"BayesFlow: Amortized Bayesian Workflows With Neural Networks","created":"2023-06-28","cited_by_count":32},{"id":"2103.10522","title":"Graphical Test for Discrete Uniformity and its Applications in Goodness of Fit Evaluation and Multiple Sample Comparison","created":"2021-03-18","cited_by_count":26},{"id":"2108.03782","title":"Pathfinder: Parallel quasi-Newton variational inference","created":"2021-08-09","cited_by_count":26},{"id":"1709.01449","title":"Visualization in Bayesian workflow","created":"2017-09-05","cited_by_count":25},{"id":"2101.10763","title":"Benchmarking Invertible Architectures on Inverse Problems","created":"2021-01-26","cited_by_count":25},{"id":"1610.05735","title":"Deep Amortized Inference for Probabilistic Programs","created":"2016-10-18","cited_by_count":23},{"id":"2004.10629","title":"Amortized Bayesian model comparison with evidential deep learning","created":"2020-04-22","cited_by_count":22},{"id":"2312.05440","title":"Consistency Models for Scalable and Fast Simulation-Based Inference","created":"2023-12-09","cited_by_count":22},{"id":"2102.06477","title":"HNPE: Leveraging Global Parameters for Neural Posterior Estimation","created":"2021-02-12","cited_by_count":19},{"id":"2111.03144","title":"Amortized Variational Inference for Simple Hierarchical Models","created":"2021-11-04","cited_by_count":19},{"id":"2211.02383","title":"Simulation-Based Calibration Checking for Bayesian Computation: The Choice of Test Quantities Shapes Sensitivity","created":"2022-11-04","cited_by_count":19},{"id":"2010.00300","title":"OutbreakFlow: Model-based Bayesian inference of disease outbreak dynamics with invertible neural networks and its application to the COVID-19 pandemics in Germany","created":"2020-10-01","cited_by_count":18},{"id":"1604.00860","title":"Bayesian Computing with INLA: A Review","created":"2016-04-04","cited_by_count":16},{"id":"2209.02439","title":"Some models are useful, but how do we know which ones? Towards a unified Bayesian model taxonomy","created":"2022-09-06","cited_by_count":16},{"id":"2101.08954","title":"Bayesian hierarchical stacking: Some models are (somewhere) useful","created":"2021-01-22","cited_by_count":14},{"id":"2310.04395","title":"Leveraging Self-Consistency for Data-Efficient Amortized Bayesian Inference","created":"2023-10-06","cited_by_count":14},{"id":"2301.11873","title":"A Deep Learning Method for Comparing Bayesian Hierarchical Models","created":"2023-01-27","cited_by_count":12},{"id":"2307.13918","title":"Simulation-based Inference for Cardiovascular Models","created":"2023-07-26","cited_by_count":11},{"id":"1905.12090","title":"Efficient Amortised Bayesian Inference for Hierarchical and Nonlinear Dynamical Systems","created":"2019-05-28","cited_by_count":10},{"id":"2002.01184","title":"tfp.mcmc: Modern Markov Chain Monte Carlo Tools Built for Modern Hardware","created":"2020-02-04","cited_by_count":10},{"id":"2006.06599","title":"Robust model training and generalisation with Studentising flows","created":"2020-06-11","cited_by_count":10},{"id":"2302.09163","title":"The Shrinkage-Delinkage Trade-off: An Analysis of Factorized Gaussian Approximations for Variational Inference","created":"2023-02-17","cited_by_count":10},{"id":"2110.13017","title":"Nested $\\hat R$: Assessing the convergence of Markov chain Monte Carlo when running many short chains","created":"2021-10-25","cited_by_count":9},{"id":"2306.12584","title":"Hierarchical Neural Simulation-Based Inference Over Event Ensembles","created":"2023-06-21","cited_by_count":9},{"id":"2110.00610","title":"Delayed rejection Hamiltonian Monte Carlo for sampling multiscale distributions","created":"2021-10-01","cited_by_count":7},{"id":"2005.03899","title":"Amortized Bayesian Inference for Models of Cognition","created":"2020-05-08","cited_by_count":6}],"next_cursor":null}