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09/17/2023
Provable learning of quantum states with graphical models
The complete learning of an n-qubit quantum state requires samples expon...
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09/02/2021
Quantum algorithm for structure learning of Markov Random Fields
Markov random fields (MRFs) appear in many problems in machine learning ...
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08/25/2020
Weakly Supervised Learning with Side Information for Noisy Labeled Images
In many real-world datasets, like WebVision, the performance of DNN base...
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11/27/2019
Bayesian inference based process design and uncertainty analysis of simulated moving bed chromatographic systems
Prominent features of simulated moving bed (SMB) chromatography processe...
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10/12/2019
Model-based process design of a ternary protein separation using multi-step gradient ion-exchange SMB chromatography
Model-based process design of ion-exchange simulated moving bed (IEX-SMB...
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02/19/2019
Variational Quantum Circuit Model for Knowledge Graphs Embedding
In this work, we propose the first quantum Ansätze for the statistical r...
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07/23/2017
Deeply-Learned Part-Aligned Representations for Person Re-Identification
In this paper, we address the problem of person re-identification, which...
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11/23/2016
Deep Convolutional Neural Networks with Merge-and-Run Mappings
A deep residual network, built by stacking a sequence of residual blocks...
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10/19/2015
DeepSaliency: Multi-Task Deep Neural Network Model for Salient Object Detection
A key problem in salient object detection is how to effectively model th...
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12/04/2014