Papers
Communities
Events
Blog
Pricing
Search
Open menu
Home
Papers
2102.05407
Cited By
Advances in Importance Sampling
10 February 2021
Victor Elvira
Luca Martino
AI4TS
Re-assign community
ArXiv
PDF
HTML
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
1
2
Next