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Boosted Generative Models
v1v2 (latest)

Boosted Generative Models

27 February 2017
Aditya Grover
Stefano Ermon
ArXiv (abs)PDFHTML

Papers citing "Boosted Generative Models"

19 / 19 papers shown
Title
Binary Losses for Density Ratio Estimation
Binary Losses for Density Ratio Estimation
Werner Zellinger
142
0
0
28 Jan 2025
NRGBoost: Energy-Based Generative Boosted Trees
NRGBoost: Energy-Based Generative Boosted Trees
João Bravo
130
0
0
04 Oct 2024
Why GANs are overkill for NLP
Why GANs are overkill for NLP
David Alvarez-Melis
Vikas Garg
Adam Tauman Kalai
60
2
0
19 May 2022
Imitating, Fast and Slow: Robust learning from demonstrations via
  decision-time planning
Imitating, Fast and Slow: Robust learning from demonstrations via decision-time planning
Carl Qi
Pieter Abbeel
Aditya Grover
OffRL
26
3
0
07 Apr 2022
Ensembles of GANs for synthetic training data generation
Ensembles of GANs for synthetic training data generation
Gabriel Eilertsen
Apostolia Tsirikoglou
Claes Lundström
Jonas Unger
MedIm
97
14
0
23 Apr 2021
DCTRGAN: Improving the Precision of Generative Models with Reweighting
DCTRGAN: Improving the Precision of Generative Models with Reweighting
S. Diefenbacher
E. Eren
Gregor Kasieczka
A. Korol
Benjamin Nachman
David Shih
78
44
0
03 Sep 2020
Telescoping Density-Ratio Estimation
Telescoping Density-Ratio Estimation
Benjamin Rhodes
Kai Xu
Michael U. Gutmann
175
97
0
22 Jun 2020
Gradient Boosted Normalizing Flows
Gradient Boosted Normalizing Flows
Robert Giaquinto
A. Banerjee
BDLDRL
16
1
0
27 Feb 2020
Fair Generative Modeling via Weak Supervision
Fair Generative Modeling via Weak Supervision
Kristy Choi
Aditya Grover
Trisha Singh
Rui Shu
Stefano Ermon
116
137
0
26 Oct 2019
Bridging the Gap Between $f$-GANs and Wasserstein GANs
Bridging the Gap Between fff-GANs and Wasserstein GANs
Jiaming Song
Stefano Ermon
105
40
0
22 Oct 2019
Understanding the Limitations of Variational Mutual Information
  Estimators
Understanding the Limitations of Variational Mutual Information Estimators
Jiaming Song
Stefano Ermon
SSLDRL
85
204
0
14 Oct 2019
Greedy Convex Ensemble
Greedy Convex Ensemble
Thanh Tan Nguyen
N. Ye
Peter L. Bartlett
48
1
0
09 Oct 2019
Neural Network based Explicit Mixture Models and
  Expectation-maximization based Learning
Neural Network based Explicit Mixture Models and Expectation-maximization based Learning
Dong Liu
Minh Thành Vu
Saikat Chatterjee
L. Rasmussen
34
2
0
31 Jul 2019
Bias Correction of Learned Generative Models using Likelihood-Free
  Importance Weighting
Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting
Aditya Grover
Jiaming Song
Alekh Agarwal
Kenneth Tran
Ashish Kapoor
Eric Horvitz
Stefano Ermon
92
125
0
23 Jun 2019
Boosting Generative Models by Leveraging Cascaded Meta-Models
Boosting Generative Models by Leveraging Cascaded Meta-Models
Fan Bao
Hang Su
Jun Zhu
26
1
0
11 May 2019
Dropout-GAN: Learning from a Dynamic Ensemble of Discriminators
Dropout-GAN: Learning from a Dynamic Ensemble of Discriminators
Gonçalo Mordido
Haojin Yang
Christoph Meinel
SyDa
98
49
0
30 Jul 2018
Variational Rejection Sampling
Variational Rejection Sampling
Aditya Grover
Ramki Gummadi
Miguel Lazaro-Gredilla
Dale Schuurmans
Stefano Ermon
BDL
126
32
0
05 Apr 2018
SGAN: An Alternative Training of Generative Adversarial Networks
SGAN: An Alternative Training of Generative Adversarial Networks
Tatjana Chavdarova
François Fleuret
GAN
76
57
0
06 Dec 2017
AdaGAN: Boosting Generative Models
AdaGAN: Boosting Generative Models
Ilya O. Tolstikhin
Sylvain Gelly
Olivier Bousquet
Carl-Johann Simon-Gabriel
Bernhard Schölkopf
GAN
100
226
0
09 Jan 2017
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