Ruikang OuYang ⚽️
Ruikang OuYang

MPhil student

About Me

Hi there 👋. I’m Tony Ruikang OuYang (歐陽瑞康 in Chinese; Seoihong AuYeung pronounced in Cantonese). Recently, I completed my MPhil in Machine Learning and Machine Intelligence from the University of Cambridge 🎉. My MPhil thesis focus on energy-based models and neural sampler for sampling from Boltzmann distribution and supervised by Prof. José Miguel Hernández-Lobato.

My current research interests span generative models, neural samplers, and their applications to molecular generation 🧬. Generally, I’m interested in probabilistic machine learning and AI4S, espesially developping powerful, efficient and scalable methods that can applied to physics ⚛️ and biochemistry 🧪.

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Interests
  • Probabilistic Machine Learning
  • Generative Models
  • Sampling Methods
  • Neural Sampler
  • AI4S (physics & biochem, etc.)
  • Geometric Deep Learning
Education
  • MPhil in Machine Learning and Machine Intelligence

    University of Cambridge

  • Visiting student in Mathematics and Statistics

    University of Oxford

  • BEng in Data Science

    Harbin Institute of Technology, shenzhen

Publications
(2024). BEnDEM: A Boltzmann Sampler Based on Bootstrapped Denoising Energy Matching. In arxiv.
(2023). L2G2G: A Scalable Local-to-Global Network Embedding with Graph Autoencoders. In CNA.
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