Advances in Importance Sampling

10 February 2021

Papers citing "Advances in Importance Sampling"

50 / 57 papers shown

Title
Direct Retrieval-augmented Optimization: Synergizing Knowledge Selection and Language Models Zhengliang Shi Lingyong Yan Weiwei Sun Yue Feng Pengjie Ren Xinyu Ma Shuaiqiang Wang D. Yin Maarten de Rijke Z. Ren RALM 43 0 0 05 May 2025
Sparse Logit Sampling: Accelerating Knowledge Distillation in LLMs Anshumann Mohd Abbas Zaidi Akhil Kedia Jinwoo Ahn Taehwak Kwon Kangwook Lee Haejun Lee Joohyung Lee FedML 107 0 0 21 Mar 2025
Mirror Online Conformal Prediction with Intermittent Feedback Bowen Wang Matteo Zecchin Osvaldo Simeone CLL 55 2 0 13 Mar 2025
A Proximal Newton Adaptive Importance Sampler Victor Elvira Émilie Chouzenoux O. Deniz Akyildiz 76 0 0 21 Dec 2024
Truncating Trajectories in Monte Carlo Policy Evaluation: an Adaptive Approach Riccardo Poiani Nicole Nobili Alberto Maria Metelli Marcello Restelli 16 0 0 17 Oct 2024
Cost-aware Simulation-based Inference Ayush Bharti Daolang Huang Samuel Kaski F. Briol 28 1 0 10 Oct 2024
Adaptive Mixture Importance Sampling for Automated Ads Auction Tuning Yimeng Jia Kaushal Paneri Rong Huang Kailash Singh Maurya Pavan Mallapragada Yifan Shi 18 0 0 20 Sep 2024
Density Ratio Estimation via Sampling along Generalized Geodesics on Statistical Manifolds Masanari Kimura H. Bondell 23 4 0 27 Jun 2024
Efficient Mixture Learning in Black-Box Variational Inference A. Hotti Oskar Kviman Ricky Molén Victor Elvira Jens Lagergren 41 1 0 11 Jun 2024
Adaptive Exploration for Data-Efficient General Value Function Evaluations Arushi Jain Josiah P. Hanna Doina Precup 26 1 0 13 May 2024
Gradient-flow adaptive importance sampling for Bayesian leave one out cross-validation for sigmoidal classification models Joshua C. Chang Xiangting Li Shixin Xu Hao-Ren Yao Julia Porcino Carson C. Chow 11 0 0 13 Feb 2024
The Definitive Guide to Policy Gradients in Deep Reinforcement Learning: Theory, Algorithms and Implementations Matthias Lehmann 28 0 0 24 Jan 2024
Variational autoencoder with weighted samples for high-dimensional non-parametric adaptive importance sampling J. Demange-Chryst F. Bachoc Jérome Morio Timothé Krauth 10 1 0 13 Oct 2023
Conditional Sampling of Variational Autoencoders via Iterated Approximate Ancestral Sampling Vaidotas Šimkus Michael U. Gutmann BDL DRL 23 3 0 17 Aug 2023
Truncating Trajectories in Monte Carlo Reinforcement Learning Riccardo Poiani Alberto Maria Metelli Marcello Restelli 8 2 0 07 May 2023
Quantile Importance Sampling J. Datta Nicholas G. Polson 25 2 0 04 May 2023
An overview of differentiable particle filters for data-adaptive sequential Bayesian inference Xiongjie Chen Yunpeng Li 12 14 0 19 Feb 2023
Unsupervised Learning of Sampling Distributions for Particle Filters Fernando Gama Nicolas Zilberstein Martín Sevilla Richard Baraniuk Santiago Segarra 33 9 0 02 Feb 2023
Stable Target Field for Reduced Variance Score Estimation in Diffusion Models Yilun Xu Shangyuan Tong Tommi Jaakkola DiffM 13 26 0 01 Feb 2023
Bayesian Self-Supervised Contrastive Learning B. Liu Bang-wei Wang Tianrui Li SSL BDL 16 4 0 27 Jan 2023
Bayesian data fusion with shared priors Peng Wu Tales Imbiriba Victor Elvira Pau Closas FedML 14 6 0 14 Dec 2022
Gradient-based Adaptive Importance Samplers Victor Elvira Émilie Chouzenoux Ömer Deniz Akyildiz Luca Martino DiffM 15 10 0 19 Oct 2022
Efficient probabilistic reconciliation of forecasts for real-valued and count time series Lorenzo Zambon Dario Azzimonti Giorgio Corani BDL AI4TS 16 5 0 05 Oct 2022
Efficient Bayes Inference in Neural Networks through Adaptive Importance Sampling Yunshi Huang Émilie Chouzenoux Victor Elvira J. Pesquet BDL 6 5 0 03 Oct 2022
Hamiltonian Adaptive Importance Sampling Ali Mousavi R. Monsefi Victor Elvira 20 13 0 27 Sep 2022
Variational Open-Domain Question Answering Valentin Liévin Andreas Geert Motzfeldt Ida Riis Jensen Ole Winther OOD BDL 26 8 0 23 Sep 2022
Adaptive importance sampling based on fault tree analysis for piecewise deterministic Markov process G. Chennetier Hassane Chraïbi A. Dutfoy Josselin Garnier 19 2 0 17 Sep 2022
Flow Annealed Importance Sampling Bootstrap Laurence Illing Midgley Vincent Stimper G. Simm Bernhard Schölkopf José Miguel Hernández-Lobato 11 77 0 03 Aug 2022
Mitigating Off-Policy Bias in Actor-Critic Methods with One-Step Q-learning: A Novel Correction Approach Baturay Saglam Dogan C. Cicek Furkan B. Mutlu Suleyman Serdar Kozat OffRL OnRL 12 1 0 01 Aug 2022
Gradients should stay on Path: Better Estimators of the Reverse- and Forward KL Divergence for Normalizing Flows Lorenz Vaitl K. Nicoli Shinichi Nakajima Pan Kessel 37 24 0 17 Jul 2022
BR-SNIS: Bias Reduced Self-Normalized Importance Sampling Gabriel Victorino Cardoso S. Samsonov Achille Thin Eric Moulines Jimmy Olsson 14 6 0 13 Jul 2022
Variance Analysis of Multiple Importance Sampling Schemes R. Mukerjee Victor Elvira 11 1 0 09 Jul 2022
Goal-Conditioned Generators of Deep Policies Francesco Faccio Vincent Herrmann Aditya A. Ramesh Louis Kirsch Jürgen Schmidhuber OffRL 14 8 0 04 Jul 2022
DELTA: Diverse Client Sampling for Fasting Federated Learning Lung-Chuang Wang Yongxin Guo Tao R. Lin Xiaoying Tang FedML 16 20 0 27 May 2022
Variance Reduction based Partial Trajectory Reuse to Accelerate Policy Gradient Optimization Hua Zheng Wei Xie 9 3 0 06 May 2022
Optimized Population Monte Carlo Victor Elvira Émilie Chouzenoux 17 23 0 14 Apr 2022
Variational methods for simulation-based inference Manuel Glöckler Michael Deistler Jakob H. Macke 19 46 0 08 Mar 2022
Multiple Importance Sampling ELBO and Deep Ensembles of Variational Approximations Oskar Kviman Harald Melin Hazal Koptagel Victor Elvira J. Lagergren DRL 63 17 0 22 Feb 2022
Policy Learning and Evaluation with Randomized Quasi-Monte Carlo Sébastien M. R. Arnold P. LÉcuyer Liyu Chen Yi-fan Chen Fei Sha OffRL 12 4 0 16 Feb 2022
Approximating Bayes in the 21st Century G. Martin David T. Frazier Christian P. Robert 27 26 0 20 Dec 2021
Adaptive Importance Sampling meets Mirror Descent: a Bias-variance tradeoff Anna Korba Franccois Portier 14 12 0 29 Oct 2021
Variance Reduction based Experience Replay for Policy Optimization Hua Zheng Wei Xie M. Feng OffRL 21 2 0 17 Oct 2021
A principled stopping rule for importance sampling Medha Agarwal Dootika Vats Victor Elvira 15 2 0 30 Aug 2021
Expectation Programming: Adapting Probabilistic Programming Systems to Estimate Expectations Efficiently Tim Reichelt Adam Goliñski C.-H. Luke Ong Tom Rainforth TPM 21 0 0 09 Jun 2021
Variational Determinant Estimation with Spherical Normalizing Flows Simon Passenheim Emiel Hoogeboom BDL 16 1 0 24 Dec 2020
Low-Variance Policy Gradient Estimation with World Models Michal Nauman Floris den Hengst OffRL 15 1 0 29 Oct 2020
Parameter-Based Value Functions Francesco Faccio Louis Kirsch Jürgen Schmidhuber OffRL 8 24 0 16 Jun 2020
Understanding the Curse of Horizon in Off-Policy Evaluation via Conditional Importance Sampling Yao Liu Pierre-Luc Bacon Emma Brunskill OffRL 6 45 0 15 Oct 2019
Amortized Monte Carlo Integration Adam Goliñski Frank D. Wood Tom Rainforth 12 4 0 18 Jul 2019
Trust-Region Variational Inference with Gaussian Mixture Models O. Arenz Mingjun Zhong Gerhard Neumann 19 18 0 10 Jul 2019