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06/16/2023
Sample-Efficient On-Policy Imitation Learning from Observations
Imitation learning from demonstrations (ILD) aims to alleviate numerous ...
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05/22/2023
Adaptive action supervision in reinforcement learning from real-world multi-agent demonstrations
Modeling of real-world biological multi-agents is a fundamental problem ...
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10/24/2022
Deep Grey-Box Modeling With Adaptive Data-Driven Models Toward Trustworthy Estimation of Theory-Driven Models
The combination of deep neural nets and theory-driven models, which we c...
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06/04/2022
Estimating counterfactual treatment outcomes over time in complex multi-agent scenarios
Evaluation of intervention in a multi-agent system, e.g., when humans sh...
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11/23/2021
Asteroid Flyby Cycler Trajectory Design Using Deep Neural Networks
Asteroid exploration has been attracting more attention in recent years....
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07/12/2021
Learning interaction rules from multi-animal trajectories via augmented behavioral models
Extracting the interaction rules of biological agents from moving sequen...
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02/25/2021
Physics-Integrated Variational Autoencoders for Robust and Interpretable Generative Modeling
Integrating physics models within machine learning holds considerable pr...
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02/19/2021
Discriminant Dynamic Mode Decomposition for Labeled Spatio-Temporal Data Collections
Extracting coherent patterns is one of the standard approaches towards u...
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07/07/2020
Policy learning with partial observation and mechanical constraints for multi-person modeling
Extracting the rules of real-world biological multi-agent behaviors is a...
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06/16/2020
Learning Dynamics Models with Stable Invariant Sets
Stable invariant sets are an essential notion in the analysis and applic...
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04/09/2020
On Anomaly Interpretation via Shapley Values
Anomaly localization is an essential problem as anomaly detection is. Be...
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09/08/2019
Shapley Values of Reconstruction Errors of PCA for Explaining Anomaly Detection
We present a method to compute the Shapley values of reconstruction erro...
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05/13/2019
Physically-interpretable classification of network dynamics for complex collective motions
Understanding complex network dynamics is a fundamental issue in various...
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02/06/2019
Regularizing Generative Models Using Knowledge of Feature Dependence
Generative modeling is a fundamental problem in machine learning with ma...
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06/29/2018
Knowledge-Based Distant Regularization in Learning Probabilistic Models
Exploiting the appropriate inductive bias based on the knowledge of data...
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05/06/2018
Dynamic and Static Topic Model for Analyzing Time-Series Document Collections
For extracting meaningful topics from texts, their structures should be ...
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11/28/2017
Recent Developments in Aerial Robotics: A Survey and Prototypes Overview
In recent years, research and development in aerial robotics (i.e., unma...
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10/12/2017
