Hayakawa, Satoshi

11 publications

ICML 2025 Distillation of Discrete Diffusion Through Dimensional Correlations Satoshi Hayakawa, Yuhta Takida, Masaaki Imaizumi, Hiromi Wakaki, Yuki Mitsufuji

ICLR 2025 Jump Your Steps: Optimizing Sampling Schedule of Discrete Diffusion Models Yong-Hyun Park, Chieh-Hsin Lai, Satoshi Hayakawa, Yuhta Takida, Yuki Mitsufuji

ICLRW 2025 Partial Alignment of Representations via Interventional Consistency Felix Leeb, Satoshi Hayakawa, Yuhta Takida, Yuki Mitsufuji

AISTATS 2024 Adaptive Batch Sizes for Active Learning: A Probabilistic Numerics Approach Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Xingchen Wan, Vu Nguyen, Harald Oberhauser, Michael A. Osborne

NeurIPSW 2024 Distillation of Discrete Diffusion Through Dimensional Correlations Satoshi Hayakawa, Yuhta Takida, Masaaki Imaizumi, Hiromi Wakaki, Yuki Mitsufuji

TMLR 2024 Policy Gradient with Kernel Quadrature Satoshi Hayakawa, Tetsuro Morimura

ICML 2023 Quantum Ridgelet Transform: Winning Lottery Ticket of Neural Networks with Quantum Computation Hayata Yamasaki, Sathyawageeswar Subramanian, Satoshi Hayakawa, Sho Sonoda

ICMLW 2023 SOBER: Highly Parallel Bayesian Optimization and Bayesian Quadrature over Discrete and Mixed Spaces Masaki Adachi, Satoshi Hayakawa, Saad Hamid, Martin Jørgensen, Harald Oberhauser, Michael A Osborne

ICML 2023 Sampling-Based Nyström Approximation and Kernel Quadrature Satoshi Hayakawa, Harald Oberhauser, Terry Lyons

NeurIPS 2022 Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel Recombination Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Harald Oberhauser, Michael A Osborne

NeurIPS 2022 Positively Weighted Kernel Quadrature via Subsampling Satoshi Hayakawa, Harald Oberhauser, Terry Lyons