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Variational inference for Monte Carlo objectives

Variational inference for Monte Carlo objectives

22 February 2016
A. Mnih
Danilo Jimenez Rezende
    DRL
    BDL
ArXivPDFHTML

Papers citing "Variational inference for Monte Carlo objectives"

50 / 183 papers shown
Title
Learning to chain-of-thought with Jensen's evidence lower bound
Learning to chain-of-thought with Jensen's evidence lower bound
Yunhao Tang
Sid Wang
Rémi Munos
BDL
OffRL
LRM
52
0
0
25 Mar 2025
Optimizing Language Models for Inference Time Objectives using Reinforcement Learning
Optimizing Language Models for Inference Time Objectives using Reinforcement Learning
Yunhao Tang
Kunhao Zheng
Gabriel Synnaeve
Rémi Munos
41
1
0
25 Mar 2025
NeuMC -- a package for neural sampling for lattice field theories
Piotr Bialas
P. Korcyl
T. Stebel
Dawid Zapolski
39
0
0
14 Mar 2025
Rateless Joint Source-Channel Coding, and a Blueprint for 6G Semantic Communications System Design
Rateless Joint Source-Channel Coding, and a Blueprint for 6G Semantic Communications System Design
Saeed R. Khosravirad
62
0
0
10 Feb 2025
Rethinking Diffusion Posterior Sampling: From Conditional Score Estimator to Maximizing a Posterior
Rethinking Diffusion Posterior Sampling: From Conditional Score Estimator to Maximizing a Posterior
Tongda Xu
Xiyan Cai
X. Zhang
Xingtong Ge
Dailan He
Ming Sun
Jingjing Liu
Y. Zhang
Jian Li
Yan Wang
DiffM
120
1
0
31 Jan 2025
Robust and highly scalable estimation of directional couplings from time-shifted signals
Robust and highly scalable estimation of directional couplings from time-shifted signals
Luca Ambrogioni
Louis Rouillard
Demian Wassermann
57
0
0
28 Jan 2025
RapGuard: Safeguarding Multimodal Large Language Models via
  Rationale-aware Defensive Prompting
RapGuard: Safeguarding Multimodal Large Language Models via Rationale-aware Defensive Prompting
Yilei Jiang
Yingshui Tan
Xiangyu Yue
KELM
LRM
41
1
0
25 Dec 2024
Streaming Bayes GFlowNets
Streaming Bayes GFlowNets
Tiago da Silva
Daniel Augusto R. M. A. de Souza
Diego Mesquita
BDL
41
0
0
08 Nov 2024
Improving Tree Probability Estimation with Stochastic Optimization and
  Variance Reduction
Improving Tree Probability Estimation with Stochastic Optimization and Variance Reduction
Tianyu Xie
Musu Yuan
Minghua Deng
Cheng Zhang
24
0
0
09 Sep 2024
Sparsifying Parametric Models with L0 Regularization
Sparsifying Parametric Models with L0 Regularization
N. Botteghi
Urban Fasel
36
0
0
05 Sep 2024
Variational Bayesian Phylogenetic Inference with Semi-implicit Branch
  Length Distributions
Variational Bayesian Phylogenetic Inference with Semi-implicit Branch Length Distributions
Tianyu Xie
Frederick A. Matsen IV
M. Suchard
Cheng Zhang
18
1
0
09 Aug 2024
Revisiting Score Function Estimators for $k$-Subset Sampling
Revisiting Score Function Estimators for kkk-Subset Sampling
Klas Wijk
Ricardo Vinuesa
Hossein Azizpour
TDI
32
1
0
22 Jul 2024
Multi-level Reliability Interface for Semantic Communications over
  Wireless Networks
Multi-level Reliability Interface for Semantic Communications over Wireless Networks
Tze-Yang Tung
H. Esfahanizadeh
Jinfeng Du
H. Viswanathan
39
1
0
07 Jul 2024
To be Continuous, or to be Discrete, Those are Bits of Questions
To be Continuous, or to be Discrete, Those are Bits of Questions
Yiran Wang
Masao Utiyama
51
2
0
12 Jun 2024
CoRMF: Criticality-Ordered Recurrent Mean Field Ising Solver
CoRMF: Criticality-Ordered Recurrent Mean Field Ising Solver
Zhenyu Pan
Ammar Gilani
En-Jui Kuo
Zhuo Liu
LRM
40
4
0
05 Mar 2024
Improving Variational Autoencoder Estimation from Incomplete Data with
  Mixture Variational Families
Improving Variational Autoencoder Estimation from Incomplete Data with Mixture Variational Families
Vaidotas Šimkus
Michael U. Gutmann
37
2
0
05 Mar 2024
Differentiable Sampling of Categorical Distributions Using the
  CatLog-Derivative Trick
Differentiable Sampling of Categorical Distributions Using the CatLog-Derivative Trick
Lennert De Smet
Emanuele Sansone
Pedro Zuidberg Dos Martires
22
11
0
21 Nov 2023
Adaptive importance sampling for heavy-tailed distributions via
  $α$-divergence minimization
Adaptive importance sampling for heavy-tailed distributions via ααα-divergence minimization
Thomas Guilmeau
Nicola Branchini
Émilie Chouzenoux
Victor Elvira
34
2
0
25 Oct 2023
ARTree: A Deep Autoregressive Model for Phylogenetic Inference
ARTree: A Deep Autoregressive Model for Phylogenetic Inference
Tianyu Xie
Cheng Zhang
20
4
0
14 Oct 2023
LL-VQ-VAE: Learnable Lattice Vector-Quantization For Efficient
  Representations
LL-VQ-VAE: Learnable Lattice Vector-Quantization For Efficient Representations
Ahmed Khalil
Robert Piechocki
Raúl Santos-Rodríguez
15
2
0
13 Oct 2023
Improved Variational Bayesian Phylogenetic Inference using Mixtures
Improved Variational Bayesian Phylogenetic Inference using Mixtures
Oskar Kviman
Ricky Molén
Jens Lagergren
15
5
0
02 Oct 2023
NAS-X: Neural Adaptive Smoothing via Twisting
NAS-X: Neural Adaptive Smoothing via Twisting
Dieterich Lawson
Michael Y. Li
Scott W. Linderman
12
1
0
28 Aug 2023
Training normalizing flows with computationally intensive target
  probability distributions
Training normalizing flows with computationally intensive target probability distributions
P. Białas
P. Korcyl
T. Stebel
13
5
0
25 Aug 2023
Renormalizing Diffusion Models
Renormalizing Diffusion Models
Jordan S. Cotler
Semon Rezchikov
DiffM
AI4CE
35
11
0
23 Aug 2023
GeoPhy: Differentiable Phylogenetic Inference via Geometric Gradients of
  Tree Topologies
GeoPhy: Differentiable Phylogenetic Inference via Geometric Gradients of Tree Topologies
Takahiro Mimori
Michiaki Hamada
18
10
0
07 Jul 2023
Variational latent discrete representation for time series modelling
Variational latent discrete representation for time series modelling
Max H. Cohen
M. Charbit
Sylvain Le Corff
25
1
0
27 Jun 2023
Resampling Gradients Vanish in Differentiable Sequential Monte Carlo
  Samplers
Resampling Gradients Vanish in Differentiable Sequential Monte Carlo Samplers
Johannes Zenn
Robert Bamler
27
3
0
27 Apr 2023
Bayesian Inference on Brain-Computer Interfaces via GLASS
Bayesian Inference on Brain-Computer Interfaces via GLASS
Bangyao Zhao
Jane E. Huggins
Jian Kang
13
0
0
14 Apr 2023
U-Statistics for Importance-Weighted Variational Inference
U-Statistics for Importance-Weighted Variational Inference
Javier Burroni
Kenta Takatsu
Justin Domke
Daniel Sheldon
13
1
0
27 Feb 2023
Learnable Topological Features for Phylogenetic Inference via Graph
  Neural Networks
Learnable Topological Features for Phylogenetic Inference via Graph Neural Networks
Cheng Zhang
15
14
0
17 Feb 2023
A Variational Perspective on Generative Flow Networks
A Variational Perspective on Generative Flow Networks
Heiko Zimmermann
Fredrik Lindsten
Jan Willem van de Meent
C. A. Naesseth
22
32
0
14 Oct 2022
GFlowNets and variational inference
GFlowNets and variational inference
Nikolay Malkin
Salem Lahlou
T. Deleu
Xu Ji
J. E. Hu
Katie Everett
Dinghuai Zhang
Yoshua Bengio
BDL
134
77
0
02 Oct 2022
Multi-Sample Training for Neural Image Compression
Multi-Sample Training for Neural Image Compression
Tongda Xu
Yan Wang
Dailan He
Chenjian Gao
Han-yi Gao
Kun Liu
Hongwei Qin
31
5
0
28 Sep 2022
Optimization of Annealed Importance Sampling Hyperparameters
Optimization of Annealed Importance Sampling Hyperparameters
Shirin Goshtasbpour
F. Pérez-Cruz
24
1
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
31
8
0
23 Sep 2022
Continuous Mixtures of Tractable Probabilistic Models
Continuous Mixtures of Tractable Probabilistic Models
Alvaro H. C. Correia
G. Gala
Erik Quaeghebeur
Cassio de Campos
Robert Peharz
TPM
11
18
0
21 Sep 2022
Latent Variable Modelling Using Variational Autoencoders: A survey
Latent Variable Modelling Using Variational Autoencoders: A survey
Vasanth Kalingeri
CML
DRL
18
2
0
20 Jun 2022
Training Discrete Deep Generative Models via Gapped Straight-Through
  Estimator
Training Discrete Deep Generative Models via Gapped Straight-Through Estimator
Ting-Han Fan
Ta-Chung Chi
Alexander I. Rudnicky
Peter J. Ramadge
BDL
27
7
0
15 Jun 2022
SIXO: Smoothing Inference with Twisted Objectives
SIXO: Smoothing Inference with Twisted Objectives
Dieterich Lawson
Allan Raventós
Andrew Warrington
Scott W. Linderman
BDL
13
15
0
13 Jun 2022
Inducing and Using Alignments for Transition-based AMR Parsing
Inducing and Using Alignments for Transition-based AMR Parsing
Andrew Drozdov
Jiawei Zhou
Radu Florian
Andrew McCallum
Tahira Naseem
Yoon Kim
Ramón Fernández Astudillo
28
27
0
03 May 2022
A Variational Approach to Bayesian Phylogenetic Inference
A Variational Approach to Bayesian Phylogenetic Inference
Cheng Zhang
IV FrederickA.Matsen
BDL
18
17
0
16 Apr 2022
Adaptive Information Bottleneck Guided Joint Source and Channel Coding
  for Image Transmission
Adaptive Information Bottleneck Guided Joint Source and Channel Coding for Image Transmission
Lunan Sun
Yang Yang
Mingzhe Chen
Caili Guo
Walid Saad
H. Vincent Poor
25
24
0
12 Mar 2022
Recursive Monte Carlo and Variational Inference with Auxiliary Variables
Recursive Monte Carlo and Variational Inference with Auxiliary Variables
Alexander K. Lew
Marco F. Cusumano-Towner
Vikash K. Mansinghka
BDL
14
10
0
05 Mar 2022
Robust PAC$^m$: Training Ensemble Models Under Misspecification and
  Outliers
Robust PACm^mm: Training Ensemble Models Under Misspecification and Outliers
Matteo Zecchin
Sangwoo Park
Osvaldo Simeone
Marios Kountouris
David Gesbert
14
5
0
03 Mar 2022
Gradient Estimation with Discrete Stein Operators
Gradient Estimation with Discrete Stein Operators
Jiaxin Shi
Yuhao Zhou
Jessica Hwang
Michalis K. Titsias
Lester W. Mackey
25
22
0
19 Feb 2022
Uphill Roads to Variational Tightness: Monotonicity and Monte Carlo
  Objectives
Uphill Roads to Variational Tightness: Monotonicity and Monte Carlo Objectives
Pierre-Alexandre Mattei
J. Frellsen
26
4
0
26 Jan 2022
A Deterministic Sampling Method via Maximum Mean Discrepancy Flow with Adaptive Kernel
A Deterministic Sampling Method via Maximum Mean Discrepancy Flow with Adaptive Kernel
Yindong Chen
Yiwei Wang
Lulu Kang
Chun Liu
18
1
0
21 Nov 2021
Entropy optimized semi-supervised decomposed vector-quantized
  variational autoencoder model based on transfer learning for multiclass text
  classification and generation
Entropy optimized semi-supervised decomposed vector-quantized variational autoencoder model based on transfer learning for multiclass text classification and generation
Shivani Malhotra
Vinay Kumar
A. K. Agarwal
DRL
11
0
0
10 Nov 2021
Double Control Variates for Gradient Estimation in Discrete Latent
  Variable Models
Double Control Variates for Gradient Estimation in Discrete Latent Variable Models
Michalis K. Titsias
Jiaxin Shi
BDL
DRL
18
5
0
09 Nov 2021
Variational Inference with Holder Bounds
Variational Inference with Holder Bounds
Junya Chen
Danni Lu
Zidi Xiu
Ke Bai
Lawrence Carin
Chenyang Tao
19
6
0
04 Nov 2021
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