Fetching the paper…
Reading the bibliography…
The solution of problems in physics is often facilitated by a change of variables.
Information theory and statistical mechanics
Jaynes, E. T · 1957
Earlier work this paper cites.
Three integrable hamiltonian systems connected with isospectral deformations
Moser, J · 1976
Earlier work this paper cites.
Integrable systems of classical mechanics and Lie algebras
Perelomov, A. M · 1990
Earlier work this paper cites.
Classical dynamics: A contemporary approach, 1998
Saletan, J. and José, J · 1998
Earlier work this paper cites.
Introduction to Classical Integrable Systems
Babelon, O., Bernard, D., Talon, M., Press, C. U., Landshoff, P., Nelson, D., Sciama, D., and Weinberg, S · 2003
Earlier work this paper cites.
Symplectic Geometry and Quantum Mechanics
de Gosson, M · 2006
Earlier work this paper cites.
The Fermi-Pasta-Ulam problem: a status report , volume 728
Gallavotti, G · 2007
Earlier work this paper cites.
The canonical coset decomposition of unitary matrices through Householder transformations
Cabrera, R., Strohecker, T., and Rabitz, H · 2010
Earlier work this paper cites.
MCMC using Hamiltonian dynamics
Neal, R. M · 2012
Earlier work this paper cites.
Mathematical methods of classical mechanics , volume 60
Arnol’d, V. I · 2013
Earlier work this paper cites.
Classical Mechanics
Goldstein, H., Poole, C., and Safko, J · 2013
Cited alongside, same era.
NICE: Non-linear Independent Components Estimation
Dinh, L., Krueger, D., and Bengio, Y · 2014
Cited alongside, same era.
Markov Chain Monte Carlo and Variational Inference: Bridging the Gap
Salimans, T., Kingma, D. P., and Welling, M · 2014
Cited alongside, same era.
Variational inference with normalizing flows
Rezende, D. J. and Mohamed, S · 2015
Cited alongside, same era.
Density estimation using Real NVP
Dinh, L., Sohl-Dickstein, J., and Bengio, S · 2016
Cited alongside, same era.
Deep Learning
Goodfellow, I., Bengio, Y., and Courville, A · 2016
Cited alongside, same era.
Understanding deep convolutional networks
The reversible residual network: Backpropagation without storing activations
Gomez, A. N., Ren, M., Urtasun, R., and Grosse, R. B · 2017
Later among the works it cites.
Generalizing hamiltonian monte carlo with neural networks
Levy, D., Hoffman, M. D., and Sohl-Dickstein, J · 2017
Later among the works it cites.
Hamiltonian variational auto-encoder
Caterini, A. L., Doucet, A., and Sejdinovic, D · 2018
Later among the works it cites.
Cohen, T. S., Geiger, M., Köhler, J., and Welling, M · 2018
Later among the works it cites.
Towards a definition of disentangled representations
Higgins, I., Amos, D., Pfau, D., Racaniere, S., Matthey, L., Rezende, D., and Lerchner, A · 2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Mallat, S · 2016
Cited alongside, same era.
Improving variational auto-encoders using householder flow
Tomczak, J. M. and Welling, M · 2016
Cited alongside, same era.
Variational inference with hamiltonian monte carlo
Wolf, C., Karl, M., and van der Smagt, P · 2016
Cited alongside, same era.
Geometric deep learning: going beyond euclidean data
Bronstein, M. M., Bruna, J., LeCun, Y., Szlam, A., and Vandergheynst, P · 2017
Cited alongside, same era.
i-revnet: Deep invertible networks
Jacobsen, J.-H., Smeulders, A., and Oyallon, E · 2018
Later among the works it cites.
Glow: Generative Flow with Invertible 1x1 Convolutions
Kingma, D. P. and Dhariwal, P · 2018
Later among the works it cites.
Greydanus, S., Dzamba, M., and Yosinski, J · 2019
Closest in time.
Neutra-lizing bad geometry in hamiltonian monte carlo using neural transport
Hoffman, M., Sountsov, P., Dillon, J. V., Langmore, I., Tran, D., and Vasudevan, S · 2019
Closest in time.