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08/15/2022
Domain-aware Control-oriented Neural Models for Autonomous Underwater Vehicles
Conventional physics-based modeling is a time-consuming bottleneck in co...
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08/03/2022
Differentiable Predictive Control with Safety Guarantees: A Control Barrier Function Approach
We develop a novel form of differentiable predictive control (DPC) with ...
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07/11/2022
Structural Inference of Networked Dynamical Systems with Universal Differential Equations
Networked dynamical systems are common throughout science in engineering...
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05/22/2022
Neural Lyapunov Differentiable Predictive Control
We present a learning-based predictive control methodology using the dif...
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03/20/2022
Neuro-physical dynamic load modeling using differentiable parametric optimization
In this work, we investigate a data-driven approach for obtaining a redu...
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03/02/2022
Learning Stochastic Parametric Differentiable Predictive Control Policies
The problem of synthesizing stochastic explicit model predictive control...
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02/28/2022
Neural Ordinary Differential Equations for Nonlinear System Identification
Neural ordinary differential equations (NODE) have been recently propose...
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07/25/2021
Deep Learning Explicit Differentiable Predictive Control Laws for Buildings
We present a differentiable predictive control (DPC) methodology for lea...
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04/08/2021
Prototypical Region Proposal Networks for Few-Shot Localization and Classification
Recently proposed few-shot image classification methods have generally f...
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01/06/2021
Constrained Block Nonlinear Neural Dynamical Models
Neural network modules conditioned by known priors can be effectively tr...
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11/26/2020
Physics-Informed Neural State Space Models via Learning and Evolution
Recent works exploring deep learning application to dynamical systems mo...
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11/26/2020
Spectral Analysis and Stability of Deep Neural Dynamics
Our modern history of deep learning follows the arc of famous emergent d...
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09/23/2020
Fuzzy Simplicial Networks: A Topology-Inspired Model to Improve Task Generalization in Few-shot Learning
Deep learning has shown great success in settings with massive amounts o...
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04/24/2020
Systematic Evaluation of Backdoor Data Poisoning Attacks on Image Classifiers
Backdoor data poisoning attacks have recently been demonstrated in compu...
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04/23/2020
Constrained Physics-Informed Deep Learning for Stable System Identification and Control of Unknown Linear Systems
This paper presents a novel data-driven method for learning deep constra...
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04/23/2020
Constrained Physics-Informed Deep Learning for Stable System Identification and Control of Linear Systems
This paper presents a novel data-driven method for learning deep constra...
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04/22/2020
Constrained Neural Ordinary Differential Equations with Stability Guarantees
Differential equations are frequently used in engineering domains, such ...
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02/17/2019
Multiple Document Representations from News Alerts for Automated Bio-surveillance Event Detection
Due to globalization, geographic boundaries no longer serve as effective...
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03/13/2018
Recurrent Neural Network Attention Mechanisms for Interpretable System Log Anomaly Detection
Deep learning has recently demonstrated state-of-the art performance on ...
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12/02/2017
Recurrent Neural Network Language Models for Open Vocabulary Event-Level Cyber Anomaly Detection
Automated analysis methods are crucial aids for monitoring and defending...
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10/02/2017