I started PhD in Machine Learning under Cambridge-Tübingen PhD Fellowship in the fall 2014, where I am co-supervised by Richard E. Turner and Zoubin Ghahramani at Cambridge, and by Bernhard Schölkopf at the Max Planck Institute for Intelligent Systems in Tübingen. I also collaborate closely with Sergey Levine at UC Berkeley. I completed my B.ASc. in Engineering Science from the University of Toronto, where I did my thesis with Prof. Geoffrey Hinton in distributed training of neural networks using evolutionary algorithms. I also had a great fortune and fun time working with Prof. Steve Mann, developing real-time HDR capture for wearable cameras/displays. I previously interned at Google Brain, hosted by Ilya Sutskever and Sergey Levine. My PhD is also jointly funded by Facebook and Kenneth-Sutherland Memorial Scholarship.
I am a member of Jesus College, Cambridge.
I am looking into machine learning involving sequential processing, such as sequence learning and reinforcement learning. I am also interested in deep learning, probabilistic models, and generative models.
- Shixiang Gu, Timothy Lillicrap, Ilya Sutskever, Sergey Levine. “Continuous Deep Q-Learning with Model-based Acceleration”. ICML 2016. [Paper]
- Shixiang Gu, Sergey Levine, Ilya Sutskever, Andriy Mnih. “MuProp: Unbiased Backpropagation for Stochastic Neural Networks”. ICLR 2016. [Paper]
- Shixiang Gu, Zoubin Ghahramani, Richard E. Turner. “Neural Adaptive Sequential Monte Carlo”. NIPS 2015. [Paper] [Supplementary]
- Nilesh Tripuraneni*, Shixiang Gu*, Hong Ge, Zoubin Ghahramani. “Particle Gibbs for Infinite Hidden Markov Models”. NIPS 2015. [Paper] *equal contribution
- Shixiang Gu, Luca Rigazio. “Toward Deep Neural Network Architectures Robust to Adversarial Examples”. ICLR 2015 Workshop. [Paper]
- Steve Mann, Raymond Chun Hing Lo, Kalin Ovtcharov, Shixiang Gu, David Dai, Calvin Ngan, Tao Ai. “Realtime HDR (High Dynamic Range) Video for EyeTap Wearable Computers, FPGA-Based Seeing Aids, and GlassEyes”, IEEE CCECE 2012, Montreal, 2012 April 29 to May 2. 6 pages, to be indexed in IEEE Xplore. ACM SIGGRAPH 2012, Emerging Technologies Exhibition. [Paper] [BibTex] [Video]
- Timothy Lillicrap, Shixiang Gu. “Deep RL methods in Robotics”. Reinforcement Learning Forum. Google, 2016.
- Shixiang Gu. “Generalized Backprop, Neural Particle Filter, and Guided Q-Learning”. Research talk hosted by Professor Pieter Abbeel. UC Berkeley, 2015.
- Shixiang Gu. “Algorithms for Training Deep Stochastic Neural Networks”. Research talk hosted by Professor Noah Goodman. Stanford University, 2015.
- Shixiang Gu, Andrey Malinin. “Long Short-Term Memory Networks”. Machine Learning RCC. Cambridge University, 2015.
My CV is here.
Email: sg717 at cam dot ac dot uk
Mail: Office BE4-40, Cambridge University Engineering Department, Trumpington Street, Cambridge CB2 1PZ, UK