Dissertation

• Modeling and control of collective dynamics: From Schroedinger bridges to Optimal Mass Transport, 2016

Journal papers

• Optimal steering of a linear stochastic system to a final probability distribution, part I
  Y. Chen, T. T. Georgiou, and M. Pavon
  IEEE Transactions on Automatic Control, 61 (5), pp. 1158-1169, 2016.

• Optimal steering of a linear stochastic system to a final probability distribution, part II
  Y. Chen, T. T. Georgiou, and M. Pavon
  IEEE Transactions on Automatic Control, 61 (5), pp. 1170-1180, 2016.

• Optimal steering of a linear stochastic system to a final probability distribution, part III
  Y. Chen, T. T. Georgiou, and M. Pavon
  IEEE Transactions on Automatic Control, 63 (9), pp. 3112 - 3118, 2018.

• On the relation between optimal transport and Schroedinger bridges: A stochastic control viewpoint
  Y. Chen, T. T. Georgiou, and M. Pavon
  Journal of Optimization Theory and Applications, 169 (2), pp. 671-691, 2016.

• Optimal transport over a linear dynamical system
  Y. Chen, T. T. Georgiou, and M. Pavon
  IEEE Transactions on Automatic Control, 62 (5), pp. 2137 -2152, 2017.

• Robust transport over networks
  Y. Chen, T. T. Georgiou, M. Pavon, and A. Tannenbaum
  IEEE Transactions on Automatic Control, 62 (9), 2017.

• Matrix Optimal Mass Transport: a Quantum Mechanical Approach
  Y. Chen, T. T. Georgiou, and A. Tannenbaum
  IEEE Transactions on Automatic Control, 63 (8), pp. 2612 - 2619, 2018.

• State tracking of linear ensembles via optimal mass transport
  Y. Chen and J. Karlsson
  IEEE Control Systems Letters, 2 (2), pp. 260 - 265, 2018.

• Vector and Matrix Optimal Mass Transport: Theory, Algorithm, and Applications
  E. K. Ryu, Y. Chen, W. Li, and S. Osher
  SIAM Journal of Scientific Computing, 40 (5), A3675 - A3698, 2018.

• Measure-valued spline curves: an optimal transport viewpoint
  Y. Chen, G. Conforti, and T. T. Georgiou
  SIAM Journal of Mathematical Analysis, 50 (6), pp. 5947 - 5968, 2018.

• Network curvature as a hallmark of brain structural connectivity
  H. Farooq, Y. Chen, T. T. Georgiou, A. Tannenbaum, and C. Lenglet
  Nature Communications, 10 (1), pp. 1 - 11, 2019.

• Hybrid block successive approximation for one-sided non-convex min-max problems: algorithms and applications
  S. Lu, I. Tsaknakis, M. Hong, and Y. Chen
  IEEE Transactions on Signal Processing, 2020.

• Optimal Steering of Ensembles With Origin-Destination Constraints
  I. Haasler, Y. Chen and J. Karlsson
  IEEE Control Systems Letters, 2020.

• Incremental Inference of Collective Graphical Models
  R. Singh, I. Haasler, Q. Zhang, J. Karlsson, and Y. Chen
  IEEE Control Systems Letters, 2020.

• Stochastic Control Liaisons: Richard Sinkhorn Meets Gaspard Monge on a Schroedinger Bridge
  Y. Chen, T. T. Georgiou, and M. Pavon
  SIAM Review, 2021.

• Multimarginal Optimal Transport with a Tree-Structured Cost and the Schroedinger Bridge Problem
  I. Haasler, A. Ringh, Y. Chen and J. Karlsson
  SIAM Journal on Control and Optimization, 2021.

• Multi-Marginal Optimal Transport and Probabilistic Graphical Models
  I. Haasler, R. Singh, Q. Zhang, J. Karlsson, and Y. Chen
  IEEE Transactions on Information Theory, 2021.

• Maximal power output of a stochastic thermodynamic engine
  R. Fu, A. Taghvaei, Y. Chen, and T. T. Georgiou
  Automatica, 2021.

• Optimal transport in systems and control
  Y. Chen, T. T. Georgiou, and M. Pavon
  Annual Review of Control, Robotics, and Autonomous Systems, 2021

• Learning Hidden Markov Models from Aggregate Observations
  R. Singh, Q. Zhang, and Y. Chen
  Automatica, 2021.

• Inference of Aggregate Hidden Markov Models with Continuous Observations
  Q. Zhang, R. Singh, and Y. Chen
  IEEE Control Systems Letters, 2022.

• Inference with Aggregate Data in Probabilistic Graphical Models: An Optimal Transport Approach
  R. Singh, I. Haasler, Q. Zhang, J.Karlsson, and Y. Chen
  IEEE Transactions on Automatic Control, 2022.

Machine learning conference papers

• Improved analysis for a proximal algorithm for sampling
  Y. Chen, S. Chewi, A. Salim, and A. Wibisono
  The 35th Annual Conference on Learning Theory, London, UK, 2022.

• Variational Wasserstein gradient flow
  J. Fan, Q. Zhang, A. Taghvaei, and Y. Chen
  Thirty-ninth International Conference on Machine Learning, Baltimore, MD, 2022.

• Path Integral Sampler: a stochastic control approach for sampling
  Q. Zhang, and Y. Chen
  Tenth International Conference on Learning Representations, 2022.

• On the complexity of the optimal transport problem with graph-structured cost
  J. Fan, I. Haasler, J. Karlsson, and Y. Chen
  25th International Conference on Artificial Intelligence and Statistics, 2022.

• Diffusion Normalizing Flow
  Q. Zhang, and Y. Chen
  2021 Conference on Neural Information Processing Systems, Online, 2021.

• Scalable Computations of Wasserstein Barycenter via Input Convex Neural Networks
  J. Fan, A. Taghvaei, and Y. Chen
  Thirty-eighth International Conference on Machine Learning (Long talk), Online, 2021.

• Can Temporal-Difference and Q-Learning Learn Representation? A Mean-Field Theory
  Y. Zhang, Q. Cai, Z. Yang, Y. Chen, and Z. Wang
  2020 Conference on Neural Information Processing Systems (ORAL), Vancouver, Canada, 2020.

• Actor-Critic Provably Finds Nash Equilibria of Linear-Quadratic Mean-Field Games
  Z. Fu, Z. Yang, Y. Chen, and Z. Wang
  Ninth International Conference on Learning Representations, Addis Ababa, Ethiopia, 2020.

• Provably Global Convergence of Actor-Critic: A Case for Linear Quadratic Regulator with Ergodic Cost
  Z. Yang, Y. Chen, M. Hong, and Z. Wang
  2019 Conference on Neural Information Processing Systems, Vancouver, Canada, 2019.

Conference papers

• Inference of collective Gaussian hidden Markov models
  R. Singh, and Y. Chen
  60th IEEE Conference on Decision and Control, Online, 2021.

• Improving Robustness via Risk Averse Distributional Reinforcement Learning
  R. Singh, Q. Zhang, and Y. Chen
  2nd Conference on Learning for Dynamics and Control, Berkeley, CA, 2020.

• Alternating Gradient Descent Ascent for Nonconvex-strongly-concave Min-Max Optimization
  S. Lu, R. Singh, X. Chen, Y. Chen, and M. Hong
  53nd Asilomar Conference on Signals, Systems and Computers, Asilomar, USA, 2019.

• Estimating Ensemble Flows on a Hidden Markov Chain
  I. Haasler, A. Ringh, Y. Chen, and J. Karlsson
  58th IEEE Conference on Decision and Control, Nice, France, 2019.

• Sample Complexity for Nonlinear Stochastic Dynamics
  Y. Chen, and U. Vaidya
  2019 American Control Conference, Philadelphia, PA, 2019.

• Matricial Wasserstein-1 Distance
  Y. Chen, T. T. Georgiou, L. Ning, and A. Tannenbaum
  56th IEEE Conference on Decision and Control, Melbourne, Australia, 2017.

• Brain Parcellation and Connectivity Mapping using Wasserstein Geometry
  H. Farooq, Y. Chen, T.T. Georgiou, and C. Lenglet
  20th International Conference on Medical Image Computing and Computer Assisted Intervention, 2017.

• Steering state statistics with output feedback
  Y. Chen, T. T. Georgiou, and M. Pavon
  in Proceedings of the 54th IEEE Conference on Decision and Control, Osaka, Japan, 2015.

• The role of past and future in estimation and the reversibility of stochastic processes
  Y. Chen, J. Karlsson, and T. T. Georgiou
  in Proceedings of the 21st International Symposium on Mathematical Theory of Networks and Systems, Groningen, The Netherlands, 2014.

• State covariances and the matrix completion problem
  Y. Chen, M. R. Jovanovic, and T. T. Georgiou
  in Proceedings of the 52nd IEEE Conference on Decision and Control , Florence, Italy, 2013.