[PDF]Adams+ (2009) The Gaussian Process Density SamplerWe are a research group working on both core methods in machine learning and artificial intelligence, as well as collaborative applications across science and engineering. Some of the topics we're interested in include automatic differentiation [1, 2] Monte Carlo methods [3, 4] Bayesian inference [5, 6] ML-accelerated design and simulation [7, 8] group symmetry in machine learning architectures [9
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https://www.ism.ac.jp/~daichi/lectures/H26-GaussianProcess/gp-lecture2-daichi.pdf
