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Advances in Importance Sampling

Advances in Importance Sampling

10 February 2021
Victor Elvira
Luca Martino
    AI4TS
ArXivPDFHTML

Papers citing "Advances in Importance Sampling"

50 / 57 papers shown
Title
Direct Retrieval-augmented Optimization: Synergizing Knowledge Selection and Language Models
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
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
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
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
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
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
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
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
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
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
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
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
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
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
Truncating Trajectories in Monte Carlo Reinforcement Learning
Riccardo Poiani
Alberto Maria Metelli
Marcello Restelli
8
2
0
07 May 2023
Quantile Importance Sampling
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
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
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
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
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
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
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
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
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
Hamiltonian Adaptive Importance Sampling
Ali Mousavi
R. Monsefi
Victor Elvira
20
13
0
27 Sep 2022
Variational Open-Domain Question Answering
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
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
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
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
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
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
Variance Analysis of Multiple Importance Sampling Schemes
R. Mukerjee
Victor Elvira
11
1
0
09 Jul 2022
Goal-Conditioned Generators of Deep Policies
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
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
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
Optimized Population Monte Carlo
Victor Elvira
Émilie Chouzenoux
17
23
0
14 Apr 2022
Variational methods for simulation-based inference
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
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
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
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
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
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
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
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
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
Low-Variance Policy Gradient Estimation with World Models
Michal Nauman
Floris den Hengst
OffRL
15
1
0
29 Oct 2020
Parameter-Based Value Functions
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
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
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
Trust-Region Variational Inference with Gaussian Mixture Models
O. Arenz
Mingjun Zhong
Gerhard Neumann
19
18
0
10 Jul 2019
12
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