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Improved off-policy training of diffusion samplers

Improved off-policy training of diffusion samplers

7 February 2024
Marcin Sendera
Minsu Kim
Sarthak Mittal
Pablo Lemos
Luca Scimeca
Jarrid Rector-Brooks
Alexandre Adam
Yoshua Bengio
Nikolay Malkin
    OffRL
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Papers citing "Improved off-policy training of diffusion samplers"

50 / 83 papers shown
Title
On scalable and efficient training of diffusion samplers
On scalable and efficient training of diffusion samplers
Minkyu Kim
Kiyoung Seong
Dongyeop Woo
SungSoo Ahn
Minsu Kim
DiffM
105
0
0
26 May 2025
Importance Weighted Score Matching for Diffusion Samplers with Enhanced Mode Coverage
Importance Weighted Score Matching for Diffusion Samplers with Enhanced Mode Coverage
Chenguang Wang
Xiaoyu Zhang
Kaiyuan Cui
Weichen Zhao
Yongtao Guan
Tianshu Yu
DiffM
55
0
0
26 May 2025
Loss-Guided Auxiliary Agents for Overcoming Mode Collapse in GFlowNets
Loss-Guided Auxiliary Agents for Overcoming Mode Collapse in GFlowNets
Idriss Malek
Abhijit Sharma
Salem Lahlou
68
0
0
21 May 2025
Ergodic Generative Flows
Ergodic Generative Flows
Leo Maxime Brunswic
Mateo Clemente
Rui Heng Yang
Adam Sigal
Amir Rasouli
Yinchuan Li
109
0
0
06 May 2025
THE-SEAN: A Heart Rate Variation-Inspired Temporally High-Order Event-Based Visual Odometry with Self-Supervised Spiking Event Accumulation Networks
Chaoran Xiong
Litao Wei
Kehui Ma
Zhen Sun
Yan Xiang
Zihan Nan
Trieu-Kien Truong
Ling Pei
87
7
0
07 Mar 2025
Posterior Inference with Diffusion Models for High-dimensional Black-box Optimization
Taeyoung Yun
Kiyoung Om
Jaewoo Lee
Sujin Yun
Jinkyoo Park
106
2
0
24 Feb 2025
In-Context Parametric Inference: Point or Distribution Estimators?
In-Context Parametric Inference: Point or Distribution Estimators?
Sarthak Mittal
Yoshua Bengio
Nikolay Malkin
Guillaume Lajoie
105
0
0
17 Feb 2025
From discrete-time policies to continuous-time diffusion samplers: Asymptotic equivalences and faster training
From discrete-time policies to continuous-time diffusion samplers: Asymptotic equivalences and faster training
Julius Berner
Lorenz Richter
Marcin Sendera
Jarrid Rector-Brooks
Nikolay Malkin
OffRL
115
8
0
10 Jan 2025
Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets
Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets
Zhen Liu
Tim Z. Xiao
Weiyang Liu
Yoshua Bengio
Dinghuai Zhang
164
5
0
10 Dec 2024
Action abstractions for amortized sampling
Action abstractions for amortized sampling
Oussama Boussif
Léna Néhale Ezzine
J. Viviano
Michał Koziarski
Moksh Jain
Nikolay Malkin
Emmanuel Bengio
Rim Assouel
Yoshua Bengio
71
0
0
19 Oct 2024
Training Neural Samplers with Reverse Diffusive KL Divergence
Training Neural Samplers with Reverse Diffusive KL Divergence
Wenlin Chen
Jiajun He
Mingtian Zhang
David Barber
José Miguel Hernández-Lobato
DiffM
92
7
0
16 Oct 2024
NETS: A Non-Equilibrium Transport Sampler
NETS: A Non-Equilibrium Transport Sampler
M. S. Albergo
Eric Vanden-Eijnden
DiffM
102
20
0
03 Oct 2024
Adaptive teachers for amortized samplers
Adaptive teachers for amortized samplers
Minsu Kim
Sanghyeok Choi
Taeyoung Yun
Emmanuel Bengio
Leo Feng
Jarrid Rector-Brooks
Sungsoo Ahn
Jinkyoo Park
Nikolay Malkin
Yoshua Bengio
438
7
0
02 Oct 2024
MetaGFN: Exploring Distant Modes with Adapted Metadynamics for Continuous GFlowNets
MetaGFN: Exploring Distant Modes with Adapted Metadynamics for Continuous GFlowNets
Dominic Phillips
F. Cipcigan
73
4
0
28 Aug 2024
Can a Bayesian Oracle Prevent Harm from an Agent?
Can a Bayesian Oracle Prevent Harm from an Agent?
Yoshua Bengio
Michael K. Cohen
Nikolay Malkin
Matt MacDermott
Damiano Fornasiere
Pietro Greiner
Younesse Kaddar
84
7
0
09 Aug 2024
Markovian Flow Matching: Accelerating MCMC with Continuous Normalizing
  Flows
Markovian Flow Matching: Accelerating MCMC with Continuous Normalizing Flows
A. Cabezas
Louis Sharrock
Christopher Nemeth
52
3
0
23 May 2024
Variational Bayesian Last Layers
Variational Bayesian Last Layers
James Harrison
John Willes
Jasper Snoek
BDL
UQCV
109
31
0
17 Apr 2024
Discrete Probabilistic Inference as Control in Multi-path Environments
Discrete Probabilistic Inference as Control in Multi-path Environments
T. Deleu
Padideh Nouri
Nikolay Malkin
Doina Precup
Yoshua Bengio
151
30
0
15 Feb 2024
Improving Gradient-guided Nested Sampling for Posterior Inference
Improving Gradient-guided Nested Sampling for Posterior Inference
Pablo Lemos
Nikolay Malkin
Will Handley
Yoshua Bengio
Y. Hezaveh
Laurence Perreault Levasseur
BDL
83
10
0
06 Dec 2023
Generative Flow Networks as Entropy-Regularized RL
Generative Flow Networks as Entropy-Regularized RL
D. Tiapkin
Nikita Morozov
Alexey Naumov
Dmitry Vetrov
69
33
0
19 Oct 2023
Learning Energy Decompositions for Partial Inference of GFlowNets
Learning Energy Decompositions for Partial Inference of GFlowNets
Hyosoon Jang
Minsu Kim
SungSoo Ahn
64
23
0
05 Oct 2023
Learning to Scale Logits for Temperature-Conditional GFlowNets
Learning to Scale Logits for Temperature-Conditional GFlowNets
Minsu Kim
Joohwan Ko
Taeyoung Yun
Dinghuai Zhang
Ling Pan
W. Kim
Jinkyoo Park
Emmanuel Bengio
Yoshua Bengio
AI4CE
79
21
0
04 Oct 2023
Local Search GFlowNets
Local Search GFlowNets
Minsu Kim
Taeyoung Yun
Emmanuel Bengio
Dinghuai Zhang
Yoshua Bengio
SungSoo Ahn
Jinkyoo Park
59
37
0
04 Oct 2023
Diffusion Generative Flow Samplers: Improving learning signals through
  partial trajectory optimization
Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization
Dinghuai Zhang
Ricky Tian Qi Chen
Cheng-Hao Liu
Aaron C. Courville
Yoshua Bengio
63
46
0
04 Oct 2023
Improved sampling via learned diffusions
Improved sampling via learned diffusions
Lorenz Richter
Julius Berner
DiffM
81
61
0
03 Jul 2023
Thompson sampling for improved exploration in GFlowNets
Thompson sampling for improved exploration in GFlowNets
Jarrid Rector-Brooks
Kanika Madan
Moksh Jain
Maksym Korablyov
Cheng-Hao Liu
Sarath Chandar
Nikolay Malkin
Yoshua Bengio
65
26
0
30 Jun 2023
Towards Understanding and Improving GFlowNet Training
Towards Understanding and Improving GFlowNet Training
Max W. Shen
Emmanuel Bengio
Ehsan Hajiramezanali
Andreas Loukas
Kyunghyun Cho
Tommaso Biancalani
43
54
0
11 May 2023
Denoising Diffusion Samplers
Denoising Diffusion Samplers
Francisco Vargas
Will Grathwohl
Arnaud Doucet
DiffM
52
87
0
27 Feb 2023
GFlowNet-EM for learning compositional latent variable models
GFlowNet-EM for learning compositional latent variable models
J. E. Hu
Nikolay Malkin
Moksh Jain
Katie Everett
Alexandros Graikos
Yoshua Bengio
CoGe
75
40
0
13 Feb 2023
DynGFN: Towards Bayesian Inference of Gene Regulatory Networks with
  GFlowNets
DynGFN: Towards Bayesian Inference of Gene Regulatory Networks with GFlowNets
Lazar Atanackovic
Alexander Tong
Bo Wang
Leo J. Lee
Yoshua Bengio
Jason S. Hartford
BDL
60
24
0
08 Feb 2023
Sample-efficient Multi-objective Molecular Optimization with GFlowNets
Sample-efficient Multi-objective Molecular Optimization with GFlowNets
Yiheng Zhu
Jialun Wu
Chaowen Hu
Jiahuan Yan
Chang-Yu Hsieh
Tingjun Hou
Jian Wu
70
35
0
08 Feb 2023
Better Training of GFlowNets with Local Credit and Incomplete
  Trajectories
Better Training of GFlowNets with Local Credit and Incomplete Trajectories
L. Pan
Nikolay Malkin
Dinghuai Zhang
Yoshua Bengio
71
68
0
03 Feb 2023
A theory of continuous generative flow networks
A theory of continuous generative flow networks
Salem Lahlou
T. Deleu
Pablo Lemos
Dinghuai Zhang
Alexandra Volokhova
Alex Hernández-García
Léna Néhale Ezzine
Yoshua Bengio
Nikolay Malkin
AI4CE
84
90
0
30 Jan 2023
Learning Interpolations between Boltzmann Densities
Learning Interpolations between Boltzmann Densities
Bálint Máté
Franccois Fleuret
86
28
0
18 Jan 2023
Robust Scheduling with GFlowNets
Robust Scheduling with GFlowNets
David W. Zhang
Corrado Rainone
M. Peschl
Roberto Bondesan
80
56
0
17 Jan 2023
A-NeSI: A Scalable Approximate Method for Probabilistic Neurosymbolic
  Inference
A-NeSI: A Scalable Approximate Method for Probabilistic Neurosymbolic Inference
Emile van Krieken
Thiviyan Thanapalasingam
Jakub M. Tomczak
F. V. Harmelen
A. T. Teije
43
38
0
23 Dec 2022
Posterior samples of source galaxies in strong gravitational lenses with
  score-based priors
Posterior samples of source galaxies in strong gravitational lenses with score-based priors
Alexandre Adam
A. Coogan
Nikolay Malkin
Ronan Legin
Laurence Perreault Levasseur
Y. Hezaveh
Yoshua Bengio
DiffM
75
23
0
07 Nov 2022
An optimal control perspective on diffusion-based generative modeling
An optimal control perspective on diffusion-based generative modeling
Julius Berner
Lorenz Richter
Karen Ullrich
DiffM
113
92
0
02 Nov 2022
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
58
35
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
184
86
0
02 Oct 2022
Learning GFlowNets from partial episodes for improved convergence and
  stability
Learning GFlowNets from partial episodes for improved convergence and stability
Kanika Madan
Jarrid Rector-Brooks
Maksym Korablyov
Emmanuel Bengio
Moksh Jain
A. Nica
Tom Bosc
Yoshua Bengio
Nikolay Malkin
63
98
0
26 Sep 2022
On free energy barriers in Gaussian priors and failure of cold start
  MCMC for high-dimensional unimodal distributions
On free energy barriers in Gaussian priors and failure of cold start MCMC for high-dimensional unimodal distributions
Afonso S. Bandeira
Antoine Maillard
Richard Nickl
Sven Wang
45
8
0
05 Sep 2022
Convergence of denoising diffusion models under the manifold hypothesis
Convergence of denoising diffusion models under the manifold hypothesis
Valentin De Bortoli
DiffM
62
168
0
10 Aug 2022
Stochastic Optimal Control for Collective Variable Free Sampling of
  Molecular Transition Paths
Stochastic Optimal Control for Collective Variable Free Sampling of Molecular Transition Paths
Lars Holdijk
Yuanqi Du
F. Hooft
P. Jaini
B. Ensing
Max Welling
26
27
0
27 Jun 2022
Torsional Diffusion for Molecular Conformer Generation
Torsional Diffusion for Molecular Conformer Generation
Bowen Jing
Gabriele Corso
Jeffrey Chang
Regina Barzilay
Tommi Jaakkola
DiffM
BDL
91
271
0
01 Jun 2022
Bayesian Structure Learning with Generative Flow Networks
Bayesian Structure Learning with Generative Flow Networks
T. Deleu
António Góis
Chris C. Emezue
M. Rankawat
Simon Lacoste-Julien
Stefan Bauer
Yoshua Bengio
BDL
85
155
0
28 Feb 2022
Generative Flow Networks for Discrete Probabilistic Modeling
Generative Flow Networks for Discrete Probabilistic Modeling
Dinghuai Zhang
Nikolay Malkin
Ziqiang Liu
Alexandra Volokhova
Aaron Courville
Yoshua Bengio
52
108
0
03 Feb 2022
Trajectory balance: Improved credit assignment in GFlowNets
Trajectory balance: Improved credit assignment in GFlowNets
Nikolay Malkin
Moksh Jain
Emmanuel Bengio
Chen Sun
Yoshua Bengio
207
180
0
31 Jan 2022
High-Resolution Image Synthesis with Latent Diffusion Models
High-Resolution Image Synthesis with Latent Diffusion Models
Robin Rombach
A. Blattmann
Dominik Lorenz
Patrick Esser
Bjorn Ommer
3DV
419
15,515
0
20 Dec 2021
Tackling the Generative Learning Trilemma with Denoising Diffusion GANs
Tackling the Generative Learning Trilemma with Denoising Diffusion GANs
Zhisheng Xiao
Karsten Kreis
Arash Vahdat
DiffM
98
552
0
15 Dec 2021
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