Fetching the paper…
Reading the bibliography…
It was recently shown that neural ordinary differential equation models cannot solve fundamental and seemingly straightforward tasks even with high-capacity vector field representations.
Beitrag zur näherungweisen integration totaler differentialgleichungen
Wilhelm Kutta · 1901
Earlier work this paper cites.
A family of embedded runge-kutta formulae
John R Dormand and Peter J Prince · 1980
Earlier work this paper cites.
An introduction to hidden markov models
Lawrence R Rabiner and Biing-Hwang Juang · 1986
Earlier work this paper cites.
Mixture density networks
Christopher M Bishop · 1994
Earlier work this paper cites.
The gronwall inequality
Ralph Howard · 1998
Earlier work this paper cites.
Probabilistic Robotics (Intelligent Robotics and Autonomous Agents)
S. Thrun, W. Burgard, and D. Fox · 2005
Earlier work this paper cites.
Numerical methods for ordinary differential equations , volume 2
John Charles Butcher and Nicolette Goodwin · 2008
Earlier work this paper cites.
Uncertain 2d vector field topology
Mathias Otto, Tobias Germer, Hans-Christian Hege, and Holger Theisel · 2010
Cited alongside, same era.
An introduction to conditional random fields
Charles Sutton, Andrew McCallum, et al · 2012
Cited alongside, same era.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
Cited alongside, same era.
Conditional random fields as recurrent neural networks
Shuai Zheng, Sadeep Jayasumana, Bernardino Romera-Paredes, Vibhav Vineet, Zhizhong Su, Dalong Du, Chang Huang, and Philip HS Torr · 2015
Cited alongside, same era.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Cited alongside, same era.
The generalized reparameterization gradient
Francisco R Ruiz, Michalis Titsias RC AUEB, and David Blei · 2016
Real-time loop closure in 2d lidar slam
Wolfgang Hess, Damon Kohler, Holger Rapp, and Daniel Andor · 2016
Later among the works it cites.
Yiping Lu, Aoxiao Zhong, Quanzheng Li, and Bin Dong · 2017
Later among the works it cites.
A proposal on machine learning via dynamical systems
E Weinan · 2017
Later among the works it cites.
Deep neural networks motivated by partial differential equations
Lars Ruthotto and Eldad Haber · 2018
Later among the works it cites.
Neural ordinary differential equations
Tian Qi Chen, Yulia Rubanova, Jesse Bettencourt, and David K Duvenaud · 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…
Cited alongside, same era.
Categorical reparameterization with gumbel-softmax
Eric Jang, Shixiang Gu, and Ben Poole · 2016
Cited alongside, same era.
Emilien Dupont, Arnaud Doucet, and Yee Whye Teh · 2019
Closest in time.
Applied Stochastic Differential Equations , volume 10
Simo Särkkä and Arno Solin · 2019
Closest in time.