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Research
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Bridging the Gap between Biological and Artificial Intelligence.
Bridging the Gap between Biological and Artificial Intelligence.
Toward a Unified Dynamical Framework of Adaptive Learning: Multi-Task Learning, Recall, Task-Switching, and More.
Toward a Unified Dynamical Framework of Adaptive Learning: Multi-Task Learning, Recall, Task-Switching, and More.
Zhixin Lu and Danielle S. Bassett. Invertible generalized synchronization: A putative mechanism for implicit learning in neural systems. Chaos: An Interdisciplinary Journal of Nonlinear Science 30, no. 6 (2020): 063133.
Toward a Neural Network Model that Modifies What's Being Learned: Translation, Rotation, and Bifurcations.
Toward a Neural Network Model that Modifies What's Being Learned: Translation, Rotation, and Bifurcations.
Jason Z. Kim, Zhixin Lu, Erfan Nozari, George J. Pappas, and Danielle S. Bassett. Teaching Recurrent Neural Networks to Modify Chaotic Memories by Example. Nature Machine Intelligence (In Press) |arXiv
Machine Learning for a Dynamic World: Prediction, Inference, Source-Separation.
Machine Learning for a Dynamic World: Prediction, Inference, Source-Separation.
Predicting the Unpredictable Future
Predicting the Unpredictable Future
Zhixin Lu, Brian R. Hunt, and Edward Ott. Attractor reconstruction by machine learning. Chaos: An Interdisciplinary Journal of Nonlinear Science 28, no. 6 (2018): 061104.
Jaideep Pathak, Zhixin Lu, Brian R. Hunt, Michelle Girvan, and Edward Ott. Using machine learning to replicate chaotic attractors and calculate Lyapunov exponents from data. Chaos: An Interdisciplinary Journal of Nonlinear Science 27, no. 12 (2017): 121102.
Jaideep Pathak, Brian Hunt, Michelle Girvan, Zhixin Lu, and Edward Ott. Model-free prediction of large spatiotemporally chaotic systems from data: A reservoir computing approach. Physical review letters 120, no. 2 (2018): 024102.
Water Knows the Answer: Source-Separation Problem Solved by a Tank of Water
Water Knows the Answer: Source-Separation Problem Solved by a Tank of Water
Zhixin Lu, Jason Z. Kim, and Danielle S. Bassett. Supervised chaotic source separation by a tank of water. Chaos: An Interdisciplinary Journal of Nonlinear Science 30, no. 2 (2020): 021101.
Seeing the Unseen: Model-Free Inference of Unmeasured Variables by Neural Networks
Seeing the Unseen: Model-Free Inference of Unmeasured Variables by Neural Networks
Zhixin Lu, Jaideep Pathak, Brian Hunt, Michelle Girvan, Roger Brockett, and Edward Ott. Reservoir observers: Model-free inference of unmeasured variables in chaotic systems. Chaos: An Interdisciplinary Journal of Nonlinear Science 27, no. 4 (2017): 041102.
Exploring Neurodynamics using Modeling Approaches and Machine Learning.
Exploring Neurodynamics using Modeling Approaches and Machine Learning.
Using Machine Learning to Discover the Causal Connectivity Matrix from Neuronal Activities.
Using Machine Learning to Discover the Causal Connectivity Matrix from Neuronal Activities.
Zhixin Lu, Jason Z. Kim, Evangelia Papadopoulos, Jennifer Stiso, Danielle S. Bassett. Using Machine Learning to Infer Causal Connectivity in Nervous System. In Preparation.
The Collective Dynamics of Pacemaker Cells Explains the East-West Asymmetry in Jet Lag Recovery.
The Collective Dynamics of Pacemaker Cells Explains the East-West Asymmetry in Jet Lag Recovery.
Zhixin Lu, Kevin Klein-Cardeña, Steven Lee, Thomas M. Antonsen, Michelle Girvan, and Edward Ott. Resynchronization of circadian oscillators and the east-west asymmetry of jet-lag. Chaos: An Interdisciplinary Journal of Nonlinear Science 26, no. 9 (2016): 094811.
Understanding the Role of Inhibitory Neurons in Facilitating Optimal Information Processing using the Mean-Field Theory.
Understanding the Role of Inhibitory Neurons in Facilitating Optimal Information Processing using the Mean-Field Theory.
Zhixin Lu, Shane Squires, Edward Ott, and Michelle Girvan. Inhibitory neurons promote robust critical firing dynamics in networks of integrate-and-fire neurons. Physical Review E 94, no. 6 (2016): 062309.
Designing Principles of Mechanical Networks and More.
Designing Principles of Mechanical Networks and More.
Design Mechanical Networks with Desired Conformational Changes.
Design Mechanical Networks with Desired Conformational Changes.
Jason Z. Kim, Zhixin Lu, Steven H. Strogatz, and Danielle S. Bassett. Conformational control of mechanical networks. Nature Physics 15, no. 7 (2019): 714-720.
Design Mechanical Networks with Desired Conformational Changes.
Design Mechanical Networks with Desired Conformational Changes.
Jason Z. Kim, Zhixin Lu, and Danielle S. Bassett. Design of large sequential conformational change in mechanical networks. Under review at the Physical Review X |arXiv
When Adibadicity Meets Topologically Forbidden Interchange of Energy Surfaces in a Hamiltonian System.
When Adibadicity Meets Topologically Forbidden Interchange of Energy Surfaces in a Hamiltonian System.
Explain why Topological Forbidden Interchange of Energy Surfaces Seemingly Happens in a Hamiltonian System with Slowly Varying Potential Wells.
Explain why Topological Forbidden Interchange of Energy Surfaces Seemingly Happens in a Hamiltonian System with Slowly Varying Potential Wells.
Zhixin Lu, Christopher Jarzynski, and Edward Ott. Apparent topologically forbidden interchange of energy surfaces under slow variation of a Hamiltonian. Physical Review E 91, no. 5 (2015): 052913.
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