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My name is Qin Wang. I am a 1st year PhD student at ETH Zürich. I received my bachelor degree in Electrical Engineering from Tsinghua Univ and my master degree from ETH Zürich.
Neural Nets, Weakly Supervised Learning and Domain Adaptation.
FPGA design, High performance computing, Power electronics.
Machine Learning and Computer Vision
- Semi-Supervised Learning by Augmented Distribution Alignment
Qin Wang, Wen Li, Luc Van Gool
Under Review, 2019 [code]
- Fully Context-Aware Video Prediction
Wonmin Byeon, Qin Wang, Rupesh Kumar Srivastava, Petros Koumoutsakos
European Conference on Computer Vision (ECCV) Oral, 2018
- Short-term Load Forecasting with Deep Residual Networks
Kunjin Chen, Kunlong Chen, Qin Wang, Ziyu He, Jun Hu, Jinliang He
IEEE Transactions on Smart Grid, 2018
- Convolutional Seq2Seq Non-intrusive Load Monitoring
Kunjin Chen, Qin Wang, Ziyu He, Kunlong Chen, Jun Hu, Jinliang He
The Journal of Engineering, 2018
- Domain Adaptive Transfer Learning for Fault Diagnosis
Qin Wang, Gabriel Michau, Olga Fink
Prognostics and System Health Management Conference, 2019
- Distribution Aligned Semi-Supervised Learning
Qin Wang, D-ITET, ETH Zurich, August 2018
- Webvision Benchmark Models
Benchmarking image classification models for Webvision Dataset: training from 16 million noisy images from the web.
Tensorflow implementation of our augmented distribution alignment method for semi-supervised learning.