Dynamic Factor Graphs for Time Series Modeling
By Piotr Wojciech Mirowski, Yann LeCun. 2009
53 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Statistical and Nonlinear Physics
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Yoshua Bengio
- Quoc V. Le
- Yann LeCun
- Sergey Levine
- Kyunghyun Cho
- Ruslan Salakhutdinov
- Mohit Bansal
- Trevor Darrell
In Statistical and Nonlinear Physics
- Justin Bayer
- Christian Osendorfer
- Yann LeCun
- Philemon Brakel
- Koray Kavukcuoglu
- Pierre Sermanet
- Vardan Papyan
- Yarin Gal
Citations in the corpus
- Variational inference of latent state sequences using Recurrent Networks (2014, background): “Based on graphical models, [19] tackles the problem from an energy-based model perspective.”
- EBLearn: Open-Source Energy-Based Learning in C++ (2009, background): “Inference consists in finding configurations of output and latent variables that minimize the energy.”
- Training energy-based models for time-series imputation (2013, background): “Certain types of Dynamical Factor Graphs (Mirowski and LeCun, 2009) are still tractable when the energy function is designed in such a way that the partition function is remains constant.”