Fetching the paper…
Reading the bibliography…
Many problems in the physical sciences, machine learning, and statistical inference necessitate sampling from a high-dimensional, multi-modal probability distribution.
1905
Earlier work this paper cites.
1910
Earlier work this paper cites.
R. Marcus, Parabolic Ito Equations, Transactions of the American Mathematical Society 198
1974
Earlier work this paper cites.
W. G. Faris and G. Jona-Lasinio, Large fluctuations for a nonlinear heat equation with noise, Journal of Physics A: Mathematical and General 15
1982
Earlier work this paper cites.
D. W. Stroock, Logarithmic Sobolev inequalities for gibbs states, in Dirichlet Forms: Lectures given at the 1st Session of the Centro Internazionale Matematico Estivo (C.I.M.E.) Held in Varenna, Italy, June 8–19, 1992 , Lecture Notes in Mathematics, edited by E. Fabes, M. Fukushima, L. Gross, C. Kenig, M. Röckner, D. W. Stroock, G. Dell’Antonio, and U. Mosco (Springer, Berlin, Heidelberg, 1993) pp. 194–228
1993
Earlier work this paper cites.
G. O. Roberts and R. L. Tweedie, Exponential convergence of Langevin distributions and their discrete approximations, Bernoulli 2
1996
Earlier work this paper cites.
H. Haario, E. Saksman, and J. Tamminen, An adaptive Metropolis algorithm, Bernoulli 7
2001
Earlier work this paper cites.
D. Frenkel and B. Smit, Understanding Molecular Simulation: From Algorithms to Applications (Elsevier, 2001)
2001
Earlier work this paper cites.
2001
Earlier work this paper cites.
P. G. Bolhuis, D. Chandler, C. Dellago, and P. L. Geissler, Transition Path Sampling: Throwing Ropes Over Rough Mountain Passes, in the Dark, Annual Review of Physical Chemistry 53
2002
Earlier work this paper cites.
2002
Earlier work this paper cites.
2002
Earlier work this paper cites.
C. Villani, Topics in Optimal Transportation , Graduate Studies in Mathematics No. 58 (American Mathematical Society, Providence, Rhode Island, 2003)
2003
Earlier work this paper cites.
2003
Earlier work this paper cites.
S. Park, M. K. Sener, D. Lu, and K. Schulten, Reaction paths based on mean first-passage times, The Journal of Chemical Physics 119
2003
Earlier work this paper cites.
W. E, W. Ren, and E. Vanden-Eijnden, Transition pathways in complex systems: Reaction coordinates, isocommittor surfaces, and transition tubes, Chem. Phys. Lett. 413
2005
Earlier work this paper cites.
C. Andrieu and É. Moulines, On the ergodicity properties of some adaptive MCMC algorithms, Annals of Applied Probability 16
2006
Earlier work this paper cites.
P. Metzner, C. Schütte, and E. Vanden-Eijnden, Illustration of transition path theory on a collection of simple examples, The Journal of Chemical Physics 125
2006
Earlier work this paper cites.
A. Jasra, D. A. Stephens, and C. C. Holmes, On population-based simulation for static inference, Statistics and Computing 17
2007
Earlier work this paper cites.
M. Hairer, An Introduction to Stochastic PDEs (2009) p. 78
2009
Cited alongside, same era.
R. J. Allen, C. Valeriani, and P. R. ten Wolde, Forward flux sampling for rare event simulations, Journal of Physics: Condensed Matter 21
2009
Cited alongside, same era.
W. E and E. Vanden-Eijnden, Transition-Path Theory and Path-Finding Algorithms for the Study of Rare Events, Annual Review of Physical Chemistry 61
2010
Cited alongside, same era.
C. Andrieu, A. Jasra, A. Doucet, and P. D. Moral, On nonlinear Markov chain Monte Carlo, Bernoulli 17
2011
Cited alongside, same era.
S. P. Meyn and R. L. Tweedie, Markov chains and stochastic stability (Springer Science & Business Media, 2012)
2012
Cited alongside, same era.
D. Levy, M. D. Hoffman, and J. Sohl-Dickstein, Generalizing Hamiltonian Monte Carlo with Neural Networks, in International Conference on Learning Representations (2018)
2018
Later among the works it cites.
T. A. Le, M. Igl, T. Rainforth, T. Jin, and F. Wood, Auto-encoding sequential monte carlo, in International Conference on Learning Representations (2018)
2018
Later among the works it cites.
2018
Later among the works it cites.
2018
Later among the works it cites.
M. S. Albergo, G. Kanwar, and P. E. Shanahan, Flow-based generative models for Markov chain Monte Carlo in lattice field theory, Physical Review D 100
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2012
Cited alongside, same era.
D. P. Kingma and M. Welling, Auto-Encoding Variational Bayes, arXiv [Preprint] 0
2013
Cited alongside, same era.
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio, Generative Adversarial Nets, in Advances in Neural Information Processing Systems 27 , edited by Z. Ghahramani, M. Welling, C. Cortes, N. D. Lawrence, and K. Q. Weinberger (Curran Associates, Inc., 2014) pp. 2672–2680
2014
Cited alongside, same era.
D. Sejdinovic, H. Strathmann, M. L. Garcia, C. Andrieu, and A. Gretton, Kernel Adaptive Metropolis-Hastings, in International Conference on Machine Learning (PMLR, 2014) pp. 1665–1673
2014
Cited alongside, same era.
M. Germain, K. Gregor, I. Murray, and H. Larochelle, MADE: Masked autoencoder for distribution estimation, in 32nd International Conference on Machine Learning, ICML 2015 , Vol. 2 (2015) pp. 881–889
2015
Cited alongside, same era.
D. Rezende and S. Mohamed, Variational Inference with Normalizing Flows, in International Conference on Machine Learning (PMLR, 2015) pp. 1530–1538
2015
Cited alongside, same era.
F. Santambrogio, Birkhäuser, Cham , Progress in Nonlinear Differential Equations and Their Applications, Vol. 87 (Springer International Publishing, Cham, 2015) p. 353
2015
Cited alongside, same era.
2019
Later among the works it cites.
D. Wu, L. Wang, and P. Zhang, Solving Statistical Mechanics Using Variational Autoregressive Networks, Physical Review Letters 122
2019
Later among the works it cites.
F. Noé, S. Olsson, J. Köhler, and H. Wu, Boltzmann generators: Sampling equilibrium states of many-body systems with deep learning, Science 365
2019
Later among the works it cites.
J. A. Carrillo, R. S. Gvalani, G. A. Pavliotis, and A. Schlichting, Long-time behaviour and phase transitions for the mckean–vlasov equation on the torus, Archive for Rational Mechanics and Analysis 235
2019
Later among the works it cites.
H. Sidky, W. Chen, and A. L. Ferguson, Molecular latent space simulators, Chemical Science 11
2020
Later among the works it cites.
K. A. Nicoli, S. Nakajima, N. Strodthoff, W. Samek, K. R. Müller, and P. Kessel, Asymptotically unbiased estimation of physical observables with neural samplers, Physical Review E 101
2020
Later among the works it cites.
H. Wu, J. Köhler, and F. Noé, Stochastic normalizing flows, in Advances in Neural Information Processing Systems , Vol. 33, edited by H. Larochelle, M. Ranzato, R. Hadsell, M. F. Balcan, and H. Lin (Curran Associates, Inc., 2020) pp. 5933–5944
2020
Later among the works it cites.
G. Falasco and M. Esposito, Dissipation-Time Uncertainty Relation, Physical Review Letters 125
2020
Later among the works it cites.
Y. Song, J. Sohl-Dickstein, D. P. Kingma, A. Kumar, S. Ermon, and B. Poole, Score-based generative modeling through stochastic differential equations, in International Conference on Learning Representations (2021)
2021
Closest in time.
G. Papamakarios, E. Nalisnick, D. J. Rezende, S. Mohamed, and B. Lakshminarayanan, Normalizing flows for probabilistic modeling and inference, Journal of Machine Learning Research 22
2021
Closest in time.
L. Sbailò, M. Dibak, and F. Noé, Neural mode jump Monte Carlo, Journal of Chemical Physics 154
2021
Closest in time.
K. A. Nicoli, C. J. Anders, L. Funcke, T. Hartung, K. Jansen, P. Kessel, S. Nakajima, and P. Stornati, Estimation of Thermodynamic Observables in Lattice Field Theories with Deep Generative Models, Physical Review Letters 126
2021
Closest in time.
2021
Closest in time.
B. Kuznets-Speck and D. T. Limmer, Dissipation bounds the amplification of transition rates far from equilibrium, Proceedings of the National Academy of Sciences 118
2021
Closest in time.