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Learning Nonlinear Dynamic Models
v1v2 (latest)

Learning Nonlinear Dynamic Models

International Conference on Machine Learning (ICML), 2009
20 May 2009
John Langford
Ruslan Salakhutdinov
Tong Zhang
ArXiv (abs)PDFHTML

Papers citing "Learning Nonlinear Dynamic Models"

18 / 18 papers shown
Stable Motion Primitives via Imitation and Contrastive Learning
Stable Motion Primitives via Imitation and Contrastive Learning
Rodrigo Pérez-Dattari
Jens Kober
429
23
0
20 Feb 2023
Imitation Learning via Simultaneous Optimization of Policies and
  Auxiliary Trajectories
Imitation Learning via Simultaneous Optimization of Policies and Auxiliary Trajectories
Mandy Xie
Anqi Li
Karl Van Wyk
F. Dellaert
Byron Boots
Nathan D. Ratliff
349
4
0
07 May 2021
A Survey on Machine Learning Applied to Dynamic Physical Systems
Sagar Verma
AI4CE
274
6
0
21 Sep 2020
Contrastive learning, multi-view redundancy, and linear models
Contrastive learning, multi-view redundancy, and linear models
Christopher Tosh
A. Krishnamurthy
Daniel J. Hsu
SSL
390
188
0
24 Aug 2020
Contrastive estimation reveals topic posterior information to linear
  models
Contrastive estimation reveals topic posterior information to linear modelsJournal of machine learning research (JMLR), 2020
Christopher Tosh
A. Krishnamurthy
Daniel J. Hsu
185
67
0
04 Mar 2020
Learning Stochastic Behaviour from Aggregate Data
Learning Stochastic Behaviour from Aggregate DataInternational Conference on Machine Learning (ICML), 2020
Shaojun Ma
Shu Liu
H. Zha
Haomin Zhou
614
18
0
10 Feb 2020
Socially Aware Kalman Neural Networks for Trajectory Prediction
Ce Ju
Zheng Wang
Xiaoyu Zhang
277
8
0
14 Sep 2018
Learning Deep Hidden Nonlinear Dynamics from Aggregate Data
Learning Deep Hidden Nonlinear Dynamics from Aggregate DataConference on Uncertainty in Artificial Intelligence (UAI), 2018
Yisen Wang
Bo Dai
Lingkai Kong
S. Erfani
James Bailey
H. Zha
DiffM
258
10
0
22 Jul 2018
A Separation Principle for Control in the Age of Deep Learning
A Separation Principle for Control in the Age of Deep Learning
Alessandro Achille
Stefano Soatto
187
32
0
09 Nov 2017
Predictive-State Decoders: Encoding the Future into Recurrent Networks
Predictive-State Decoders: Encoding the Future into Recurrent Networks
Arun Venkatraman
Nicholas Rhinehart
Wen Sun
Lerrel Pinto
M. Hebert
Byron Boots
Kris Kitani
J. Andrew Bagnell
AI4CE
263
43
0
25 Sep 2017
Practical Learning of Predictive State Representations
Practical Learning of Predictive State Representations
Carlton Downey
Ahmed S. Hefny
Geoffrey J. Gordon
190
11
0
14 Feb 2017
An Efficient, Expressive and Local Minima-free Method for Learning
  Controlled Dynamical Systems
An Efficient, Expressive and Local Minima-free Method for Learning Controlled Dynamical SystemsAAAI Conference on Artificial Intelligence (AAAI), 2017
Ahmed S. Hefny
Carlton Downey
Geoffrey J. Gordon
228
6
0
12 Feb 2017
Learning to Filter with Predictive State Inference Machines
Learning to Filter with Predictive State Inference Machines
Wen Sun
Arun Venkatraman
Byron Boots
J. Andrew Bagnell
AI4CE
222
52
0
30 Dec 2015
Deep Kalman Filters
Deep Kalman Filters
Rahul G. Krishnan
Uri Shalit
David Sontag
BDLAI4TS
413
416
0
16 Nov 2015
Embed to Control: A Locally Linear Latent Dynamics Model for Control
  from Raw Images
Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images
Manuel Watter
Jost Tobias Springenberg
Joschka Boedecker
Martin Riedmiller
BDL
754
895
0
24 Jun 2015
The LICORS Cabinet: Nonparametric Algorithms for Spatio-temporal
  Prediction
The LICORS Cabinet: Nonparametric Algorithms for Spatio-temporal PredictionIEEE International Joint Conference on Neural Network (IJCNN), 2015
George D. Montañez
C. Shalizi
AI4TS
248
3
0
08 Jun 2015
Supervised Learning for Dynamical System Learning
Supervised Learning for Dynamical System Learning
Ahmed S. Hefny
Carlton Downey
Geoffrey J. Gordon
161
3
0
20 May 2015
Reduced-Rank Hidden Markov Models
Reduced-Rank Hidden Markov Models
S. Siddiqi
Byron Boots
Geoffrey J. Gordon
BDL
631
137
0
06 Oct 2009
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