Person
Young Jun Ko
This person is no longer with EPFL
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Related publications (7)
Please note that this is not a complete list of this person’s publications. It includes only semantically relevant works. For a full list, please refer to Infoscience.
Revealing the Surface Chemistry for CO2 Hydrogenation on Cu/CeO2–x Using Near-Ambient-Pressure X-ray Photoelectron Spectroscopy
Andreas Züttel, Emad Oveisi, Thi Ha My Pham, Wen Luo, Mo Li, Young Jun Ko
Catalytic reduction of CO2 to valuable products is an attractive route for CO2 recycling. CeO2-supported Cu catalysts have shown high activity and selectivity for the hydrogenation of CO2 to CO. To uncover the origin of their high performance, we prepared ...
ACS2021Applications of Approximate Learning and Inference for Probabilistic Models
We develop approximate inference and learning methods for facilitating the use of probabilistic modeling techniques motivated by applications in two different areas. First, we consider the ill-posed inverse problem of recovering an image from an underdeter ...
EPFL2017Collaborative Recurrent Neural Networks for Dynamic Recommender Systems
Matthias Grossglauser, Lucas Maystre, Young Jun Ko
Modern technologies enable us to record sequences of online user activity at an unprecedented scale. Although such activity logs are abundantly available, most approaches to recommender systems are based on the rating-prediction paradigm, ignoring temporal ...
2016