Noticias en español
— Associate Researchers
PhD in Electrical Engineering, Universidad de Chile (2017)
Bachelor of Engineering, Mechatronics, The University of Newcastle, Australia (2011)
Bachelor of Engineering, Mechatronics, The University of Newcastle, Australia (2011)
Institution: Universidad de Chile
Works at:
CMM Data Science
CMM Data Science
Research interests:
Focusing on Geometric Deep Learning and Information Theoretic Measures in deep learning including:
- Lossy compression for unsupervised anomaly detection
- Graph neural networks
- Neural Algorithmic Reasoning
- Reinforcement Learning (Deep Q-Learning Networks; DQN) jointly with World Generators (transferable reinforcement learning)
- Imitation Learning of Process Control Systems (Deep Q-Learning from Demonstrations) for a transferable prior for a DQN agent.
- XLVIN
Focusing on Geometric Deep Learning and Information Theoretic Measures in deep learning including:
- Lossy compression for unsupervised anomaly detection
- Graph neural networks
- Neural Algorithmic Reasoning
- Reinforcement Learning (Deep Q-Learning Networks; DQN) jointly with World Generators (transferable reinforcement learning)
- Imitation Learning of Process Control Systems (Deep Q-Learning from Demonstrations) for a transferable prior for a DQN agent.
- XLVIN
cley (at) cmm.uchile.cl
office: 710
office: 710
Bio:
First Place in the Doctoral Symposium, Best Effort & Presentation, PHM Society (The Prognostics and Health Management Society), awarded October 2015.
ResearchGate ProfileFirst Place in the Doctoral Symposium, Best Effort & Presentation, PHM Society (The Prognostics and Health Management Society), awarded October 2015.
