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09/06/2023
Combining Thermodynamics-based Model of the Centrifugal Compressors and Active Machine Learning for Enhanced Industrial Design Optimization
The design process of centrifugal compressors requires applying an optim...
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08/04/2022
Deep Surrogate of Modular Multi Pump using Active Learning
Due to the high cost and reliability of sensors, the designers of a pump...
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09/21/2018
Constrained Exploration and Recovery from Experience Shaping
We consider the problem of reinforcement learning under safety requireme...
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08/07/2018
Deep Learning with Predictive Control for Human Motion Tracking
We propose to combine model predictive control with deep learning for th...
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07/18/2018
Experimental Force-Torque Dataset for Robot Learning of Multi-Shape Insertion
Most real-world systems are complex and hard to model accurately. Machin...
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07/04/2018
Transfer Learning From Synthetic To Real Images Using Variational Autoencoders For Precise Position Detection
Capturing and labeling camera images in the real world is an expensive t...
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06/22/2018
Focusing on What is Relevant: Time-Series Learning and Understanding using Attention
This paper is a contribution towards interpretability of the deep learni...
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06/03/2018
MaestROB: A Robotics Framework for Integrated Orchestration of Low-Level Control and High-Level Reasoning
This paper describes a framework called MaestROB. It is designed to make...
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09/22/2017
OptLayer - Practical Constrained Optimization for Deep Reinforcement Learning in the Real World
While deep reinforcement learning techniques have recently produced cons...
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09/20/2017
Transfer learning from synthetic to real images using variational autoencoders for robotic applications
Robotic learning in simulation environments provides a faster, more scal...
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08/16/2017
Limiting the Reconstruction Capability of Generative Neural Network using Negative Learning
Generative models are widely used for unsupervised learning with various...
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08/14/2017