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2402.05098
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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 / 95 papers shown
Diffusion Fine-Tuning via Reparameterized Policy Gradient of the Soft Q-Function
Hyeongyu Kang
Jaewoo Lee
Woocheol Shin
Kiyoung Om
Jinkyoo Park
188
1
0
04 Dec 2025
Reinforced sequential Monte Carlo for amortised sampling
Sanghyeok Choi
Sarthak Mittal
Victor Elvira
Jinkyoo Park
Nikolay Malkin
171
1
0
13 Oct 2025
Data-to-Energy Stochastic Dynamics
Kirill Tamogashev
Nikolay Malkin
DiffM
186
2
0
30 Sep 2025
Trust Region Constrained Measure Transport in Path Space for Stochastic Optimal Control and Inference
Denis Blessing
Julius Berner
Lorenz Richter
Carles Domingo-Enrich
Yuanqi Du
Arash Vahdat
Gerhard Neumann
164
13
0
17 Aug 2025
Rethinking Losses for Diffusion Bridge Samplers
Sebastian Sanokowski
Lukas Gruber
Christoph Bartmann
Sepp Hochreiter
Sebastian Lehner
DiffM
431
6
0
12 Jun 2025
Progressive Tempering Sampler with Diffusion
Severi Rissanen
RuiKang OuYang
Jiajun He
Wenlin Chen
Markus Heinonen
Arno Solin
José Miguel Hernández-Lobato
DiffM
363
9
0
05 Jun 2025
Adaptive Destruction Processes for Diffusion Samplers
Timofei Gritsaev
Nikita Morozov
Kirill Tamogashev
D. Tiapkin
S. Samsonov
A. Naumov
Dmitry Vetrov
Nikolay Malkin
359
5
0
02 Jun 2025
Importance Weighted Score Matching for Diffusion Samplers with Enhanced Mode Coverage
Chenguang Wang
Xiaoyu Zhang
Kaiyuan Cui
Weichen Zhao
Yongtao Guan
Tianshu Yu
DiffM
383
2
0
26 May 2025
On scalable and efficient training of diffusion samplers
Minkyu Kim
Kiyoung Seong
Dongyeop Woo
SungSoo Ahn
Minsu Kim
DiffM
553
8
0
26 May 2025
Energy-based generator matching: A neural sampler for general state space
Dongyeop Woo
Minsu Kim
Minkyu Kim
Kiyoung Seong
SungSoo Ahn
622
2
0
26 May 2025
Loss-Guided Auxiliary Agents for Overcoming Mode Collapse in GFlowNets
Idriss Malek
Abhijit Sharma
Abhijith Sharma
Eric Moulines
Salem Lahlou
356
2
0
21 May 2025
Ergodic Generative Flows
Leo Maxime Brunswic
Mateo Clemente
Rui Heng Yang
Adam Sigal
Amir Rasouli
Yinchuan Li
326
2
0
06 May 2025
Trajectory Balance with Asynchrony: Decoupling Exploration and Learning for Fast, Scalable LLM Post-Training
Brian Bartoldson
S. Venkatraman
James Diffenderfer
Moksh Jain
Tal Ben-Nun
Seanie Lee
Minsu Kim
J. Obando-Ceron
Yoshua Bengio
B. Kailkhura
OffRL
423
22
0
24 Mar 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
278
39
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
528
6
0
24 Feb 2025
Maximum Entropy Reinforcement Learning with Diffusion Policy
Xiaoyi Dong
Jian Cheng
Xinsong Zhang
605
23
0
17 Feb 2025
In-Context Parametric Inference: Point or Distribution Estimators?
Sarthak Mittal
Yoshua Bengio
Nikolay Malkin
Guillaume Lajoie
355
2
0
17 Feb 2025
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
592
15
0
10 Jan 2025
Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets
International Conference on Learning Representations (ICLR), 2024
Zhen Liu
Tim Z. Xiao
Weiyang Liu
Yoshua Bengio
Dinghuai Zhang
788
25
0
10 Dec 2024
Action abstractions for amortized sampling
International Conference on Learning Representations (ICLR), 2024
Oussama Boussif
Léna Néhale Ezzine
J. Viviano
Michał Koziarski
Moksh Jain
Nikolay Malkin
Emmanuel Bengio
Rim Assouel
Yoshua Bengio
261
3
0
19 Oct 2024
Training Neural Samplers with Reverse Diffusive KL Divergence
International Conference on Artificial Intelligence and Statistics (AISTATS), 2024
Wenlin Chen
Jiajun He
Mingtian Zhang
David Barber
José Miguel Hernández-Lobato
DiffM
444
19
0
16 Oct 2024
U-net based prediction of cerebrospinal fluid distribution and ventricular reflux grading
NMR in Biomedicine (NMR Biomed), 2024
Melanie Rieff
Fabian Holzberger
Oksana Lapina
Geir Ringstad
Lars Magnus Valnes
Bogna Warsza
Kent-Andre Mardal
Per Kristian Eide
Barbara Wohlmuth
450
11
0
06 Oct 2024
NETS: A Non-Equilibrium Transport Sampler
M. S. Albergo
Eric Vanden-Eijnden
DiffM
536
54
0
03 Oct 2024
Adaptive teachers for amortized samplers
International Conference on Learning Representations (ICLR), 2024
Minsu Kim
Sanghyeok Choi
Taeyoung Yun
Emmanuel Bengio
Leo Feng
Jarrid Rector-Brooks
Sungsoo Ahn
Jinkyoo Park
Nikolay Malkin
Yoshua Bengio
986
22
0
02 Oct 2024
MetaGFN: Exploring Distant Modes with Adapted Metadynamics for Continuous GFlowNets
Dominic Phillips
F. Cipcigan
455
7
0
28 Aug 2024
Can a Bayesian Oracle Prevent Harm from an Agent?
Conference on Uncertainty in Artificial Intelligence (UAI), 2024
Yoshua Bengio
Michael K. Cohen
Nikolay Malkin
Matt MacDermott
Damiano Fornasiere
Pietro Greiner
Younesse Kaddar
472
9
0
09 Aug 2024
Markovian Flow Matching: Accelerating MCMC with Continuous Normalizing Flows
Neural Information Processing Systems (NeurIPS), 2024
A. Cabezas
Louis Sharrock
Christopher Nemeth
283
8
0
23 May 2024
Variational Bayesian Last Layers
James Harrison
John Willes
Jasper Snoek
BDL
UQCV
441
74
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17 Apr 2024
Discrete Probabilistic Inference as Control in Multi-path Environments
T. Deleu
Padideh Nouri
Nikolay Malkin
Doina Precup
Yoshua Bengio
431
42
0
15 Feb 2024
Improving Gradient-guided Nested Sampling for Posterior Inference
Pablo Lemos
Nikolay Malkin
Will Handley
Yoshua Bengio
Y. Hezaveh
Laurence Perreault Levasseur
BDL
250
15
0
06 Dec 2023
Generative Flow Networks as Entropy-Regularized RL
D. Tiapkin
Nikita Morozov
Alexey Naumov
Dmitry Vetrov
408
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0
19 Oct 2023
Learning Energy Decompositions for Partial Inference of GFlowNets
International Conference on Learning Representations (ICLR), 2023
Hyosoon Jang
Minsu Kim
SungSoo Ahn
289
32
0
05 Oct 2023
Learning to Scale Logits for Temperature-Conditional GFlowNets
International Conference on Machine Learning (ICML), 2023
Minsu Kim
Joohwan Ko
Taeyoung Yun
Dinghuai Zhang
Ling Pan
W. Kim
Jinkyoo Park
Emmanuel Bengio
Yoshua Bengio
AI4CE
393
30
0
04 Oct 2023
Local Search GFlowNets
International Conference on Learning Representations (ICLR), 2023
Minsu Kim
Taeyoung Yun
Emmanuel Bengio
Dinghuai Zhang
Yoshua Bengio
SungSoo Ahn
Jinkyoo Park
403
58
0
04 Oct 2023
Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization
International Conference on Learning Representations (ICLR), 2023
Dinghuai Zhang
Ricky Tian Qi Chen
Cheng-Hao Liu
Aaron C. Courville
Yoshua Bengio
473
64
0
04 Oct 2023
Improved sampling via learned diffusions
International Conference on Learning Representations (ICLR), 2023
Lorenz Richter
Julius Berner
DiffM
472
100
0
03 Jul 2023
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
254
37
0
30 Jun 2023
torchgfn: A PyTorch GFlowNet library
J. Viviano
Omar G. Younis
Sanghyeok Choi
Victor Schmidt
Yoshua Bengio
Salem Lahlou
OOD
AI4CE
406
8
0
24 May 2023
Towards Understanding and Improving GFlowNet Training
International Conference on Machine Learning (ICML), 2023
Max W. Shen
Emmanuel Bengio
Ehsan Hajiramezanali
Andreas Loukas
Kyunghyun Cho
Tommaso Biancalani
274
80
0
11 May 2023
Denoising Diffusion Samplers
International Conference on Learning Representations (ICLR), 2023
Francisco Vargas
Will Grathwohl
Arnaud Doucet
DiffM
435
134
0
27 Feb 2023
GFlowNet-EM for learning compositional latent variable models
International Conference on Machine Learning (ICML), 2023
J. E. Hu
Nikolay Malkin
Moksh Jain
Katie Everett
Alexandros Graikos
Yoshua Bengio
CoGe
307
48
0
13 Feb 2023
DynGFN: Towards Bayesian Inference of Gene Regulatory Networks with GFlowNets
Neural Information Processing Systems (NeurIPS), 2023
Lazar Atanackovic
Alexander Tong
Bo Wang
Leo J. Lee
Yoshua Bengio
Jason S. Hartford
BDL
396
33
0
08 Feb 2023
Sample-efficient Multi-objective Molecular Optimization with GFlowNets
Neural Information Processing Systems (NeurIPS), 2023
Yiheng Zhu
Jialun Wu
Chaowen Hu
Jiahuan Yan
Chang-Yu Hsieh
Tingjun Hou
Jian Wu
476
62
0
08 Feb 2023
Better Training of GFlowNets with Local Credit and Incomplete Trajectories
International Conference on Machine Learning (ICML), 2023
L. Pan
Nikolay Malkin
Dinghuai Zhang
Yoshua Bengio
332
98
0
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A theory of continuous generative flow networks
International Conference on Machine Learning (ICML), 2023
Salem Lahlou
T. Deleu
Pablo Lemos
Dinghuai Zhang
Alexandra Volokhova
Alex Hernández-García
Léna Néhale Ezzine
Yoshua Bengio
Nikolay Malkin
AI4CE
397
117
0
30 Jan 2023
Learning Interpolations between Boltzmann Densities
Bálint Máté
Franccois Fleuret
590
41
0
18 Jan 2023
Robust Scheduling with GFlowNets
International Conference on Learning Representations (ICLR), 2023
David W. Zhang
Corrado Rainone
M. Peschl
Roberto Bondesan
472
72
0
17 Jan 2023
A-NeSI: A Scalable Approximate Method for Probabilistic Neurosymbolic Inference
Neural Information Processing Systems (NeurIPS), 2022
Emile van Krieken
Thiviyan Thanapalasingam
Jakub M. Tomczak
F. V. Harmelen
A. T. Teije
472
52
0
23 Dec 2022
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
198
28
0
07 Nov 2022
An optimal control perspective on diffusion-based generative modeling
Julius Berner
Lorenz Richter
Karen Ullrich
DiffM
535
140
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02 Nov 2022
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