Ge, Hong

11 publications

NeurIPS 2024 Neural Characteristic Activation Analysis and Geometric Parameterization for ReLU Networks Wenlin Chen, Hong Ge

JMLR 2024 Numerically Stable Sparse Gaussian Processes via Minimum Separation Using Cover Trees Alexander Terenin, David R. Burt, Artem Artemev, Seth Flaxman, Mark van der Wilk, Carl Edward Rasmussen, Hong Ge

ICML 2024 Practical Hamiltonian Monte Carlo on Riemannian Manifolds via Relativity Theory Kai Xu, Hong Ge

ICMLW 2024 ReLU Characteristic Activation Analysis Wenlin Chen, Hong Ge

ICMLW 2023 Beyond Intuition, a Framework for Applying GPs to Real-World Data Kenza Tazi, Jihao Andreas Lin, Ross Viljoen, Alex Gardner, S. T. John, Hong Ge, Richard E Turner

NeurIPSW 2022 Learning Deep Neural Networks by Iterative Linearisation Adrian Goldwaser, Hong Ge

AISTATS 2021 Couplings for Multinomial Hamiltonian Monte Carlo Kai Xu, Tor Erlend Fjelde, Charles Sutton, Hong Ge

NeurIPS 2019 Bayesian Learning of Sum-Product Networks Martin Trapp, Robert Peharz, Hong Ge, Franz Pernkopf, Zoubin Ghahramani

AISTATS 2018 Turing: Composable Inference for Probabilistic Programming Hong Ge, Kai Xu, Zoubin Ghahramani

ICML 2015 Distributed Inference for Dirichlet Process Mixture Models Hong Ge, Yutian Chen, Moquan Wan, Zoubin Ghahramani

NeurIPS 2015 Particle Gibbs for Infinite Hidden Markov Models Nilesh Tripuraneni, Shixiang Gu, Hong Ge, Zoubin Ghahramani