Harmonizable mixture kernels with variational Fourier features. - Zheyang Shen; Markus Heinonen; Samuel Kaski (AISTATS, 2019)

Learning spectrograms with convolutional spectral kernels. - Zheyang Shen; Markus Heinonen; Samuel Kaski (AISTATS, 2020)

Rethinking Sparse Gaussian Processes: Bayesian Approaches to Inducing-Variable Approximations. - Simone Rossi 001; Markus Heinonen; Edwin V. Bonilla; Zheyang Shen; Maurizio Filippone (CoRR, 2020)

Sparse Gaussian Processes Revisited: Bayesian Approaches to Inducing-Variable Approximations. - Simone Rossi 001; Markus Heinonen; Edwin V. Bonilla; Zheyang Shen; Maurizio Filippone (AISTATS, 2021)

De-randomizing MCMC dynamics with the diffusion Stein operator. - Zheyang Shen; Markus Heinonen; Samuel Kaski (NeurIPS, 2021)

Operator-informed score matching for Markov diffusion models. - Zheyang Shen; Chris J. Oates (CoRR, 2024)

Prediction-Centric Uncertainty Quantification via MMD. - Zheyang Shen; Jeremias Knoblauch; Samuel Power; Chris J. Oates (AISTATS, 2025)

Gaussian Processes with Bayesian Inference of Covariate Couplings. - Mattia Rosso; Juho Ylä-Jääski; Zheyang Shen; Markus Heinonen; Maurizio Filippone (Trans. Mach. Learn. Res., 2025)