Yang, Hongseok

29 publications

NeurIPS 2025 Axial Neural Networks for Dimension-Free Foundation Models Hyunsu Kim, Jonggeon Park, Joan Bruna, Hongseok Yang, Juho Lee

TMLR 2025 Over-Parameterised Shallow Neural Networks with Asymmetrical Node Scaling: Global Convergence Guarantees and Feature Learning Francois Caron, Fadhel Ayed, Paul Jung, Hoil Lee, Juho Lee, Hongseok Yang

ICLR 2025 Parameter Expanded Stochastic Gradient Markov Chain Monte Carlo Hyunsu Kim, Giung Nam, Chulhee Yun, Hongseok Yang, Juho Lee

ICML 2024 An Infinite-Width Analysis on the Jacobian-Regularised Training of a Neural Network Taeyoung Kim, Hongseok Yang

ICMLW 2024 Analysing Feature Learning of Gradient Descent Using Periodic Functions Jaehui Hwang, Taeyoung Kim, Hongseok Yang

NeurIPS 2024 Mitigating Covariate Shift in Behavioral Cloning via Robust Stationary Distribution Correction Seokin Seo, Byung-Jun Lee, Jongmin Lee, HyeongJoo Hwang, Hongseok Yang, Kee-Eung Kim

ICMLW 2024 Transformers Can Perform Distributionally-Robust Optimisation Through In-Context Learning Taeyoung Kim, Hongseok Yang

ICML 2024 Variational Partial Group Convolutions for Input-Aware Partial Equivariance of Rotations and Color-Shifts Hyunsu Kim, Yegon Kim, Hongseok Yang, Juho Lee

JMLR 2023 Deep Neural Networks with Dependent Weights: Gaussian Process Mixture Limit, Heavy Tails, Sparsity and Compressibility Hoil Lee, Fadhel Ayed, Paul Jung, Juho Lee, Hongseok Yang, Francois Caron

NeurIPSW 2023 Deep Neural Networks with Dependent Weights: \\Gaussian Process Mixture Limit, Heavy Tails, Sparsity and Compressibility Hoil Lee, Fadhel Ayed, Paul Jung, Juho Lee, Hongseok Yang, Francois Caron

NeurIPSW 2023 Learning Symmetrization for Equivariance with Orbit Distance Minimization Dat Tien Nguyen, Jinwoo Kim, Hongseok Yang, Seunghoon Hong

NeurIPSW 2023 Over-Parameterised Shallow Neural Networks with Asymmetrical Node Scaling: \\ Global Convergence Guarantees and Feature Learning Fadhel Ayed, Francois Caron, Paul Jung, Juho Lee, Hoil Lee, Hongseok Yang

NeurIPS 2023 Regularized Behavior Cloning for Blocking the Leakage of past Action Information Seokin Seo, HyeongJoo Hwang, Hongseok Yang, Kee-Eung Kim

ICML 2023 Regularizing Towards Soft Equivariance Under Mixed Symmetries Hyunsu Kim, Hyungi Lee, Hongseok Yang, Juho Lee

ICLR 2022 DemoDICE: Offline Imitation Learning with Supplementary Imperfect Demonstrations Geon-Hyeong Kim, Seokin Seo, Jongmin Lee, Wonseok Jeon, HyeongJoo Hwang, Hongseok Yang, Kee-Eung Kim

NeurIPS 2022 Learning Symmetric Rules with SATNet Sangho Lim, Eun-Gyeol Oh, Hongseok Yang

NeurIPS 2022 LobsDICE: Offline Learning from Observation via Stationary Distribution Correction Estimation Geon-Hyeong Kim, Jongmin Lee, Youngsoo Jang, Hongseok Yang, Kee-Eung Kim

ICLR 2022 Scale Mixtures of Neural Network Gaussian Processes Hyungi Lee, Eunggu Yun, Hongseok Yang, Juho Lee

NeurIPSW 2021 Meta-Learning an Inference Algorithm for Probabilistic Programs Gwonsoo Che, Hongseok Yang

ICML 2021 Probabilistic Programs with Stochastic Conditioning David Tolpin, Yuan Zhou, Tom Rainforth, Hongseok Yang

AAAI 2020 Differentiable Algorithm for Marginalising Changepoints Hyoungjin Lim, Gwonsoo Che, Wonyeol Lee, Hongseok Yang

ICML 2020 Divide, Conquer, and Combine: A New Inference Strategy for Probabilistic Programs with Stochastic Support Yuan Zhou, Hongseok Yang, Yee Whye Teh, Tom Rainforth

NeurIPS 2020 On Correctness of Automatic Differentiation for Non-Differentiable Functions Wonyeol Lee, Hangyeol Yu, Xavier Rival, Hongseok Yang

ICML 2020 Variational Inference for Sequential Data with Future Likelihood Estimates Geon-Hyeong Kim, Youngsoo Jang, Hongseok Yang, Kee-Eung Kim

AISTATS 2019 LF-PPL: A Low-Level First Order Probabilistic Programming Language for Non-Differentiable Models Yuan Zhou, Bradley J. Gram-Hansen, Tobias Kohn, Tom Rainforth, Hongseok Yang, Frank Wood

ACML 2019 Trust Region Sequential Variational Inference Geon-Hyeong Kim, Youngsoo Jang, Jongmin Lee, Wonseok Jeon, Hongseok Yang, Kee-Eung Kim

ICML 2018 On Nesting Monte Carlo Estimators Tom Rainforth, Rob Cornish, Hongseok Yang, Andrew Warrington, Frank Wood

NeurIPS 2018 Reparameterization Gradient for Non-Differentiable Models Wonyeol Lee, Hangyeol Yu, Hongseok Yang

AISTATS 2015 Particle Gibbs with Ancestor Sampling for Probabilistic Programs Jan-Willem van de Meent, Hongseok Yang, Vikash Mansinghka, Frank D. Wood