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Futoshi Futami
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Year
Variational inference based on robust divergences
F Futami, I Sato, M Sugiyama
International Conference on Artificial Intelligence and Statistics, 813-822, 2018
732018
Bayesian posterior approximation via greedy particle optimization
F Futami, Z Cui, I Sato, M Sugiyama
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 3606-3613, 2019
222019
Accelerating the diffusion-based ensemble sampling by non-reversible dynamics
F Futami, I Sato, M Sugiyama
International Conference on Machine Learning, 2020, 2020
152020
Accelerated diffusion-based sampling by the non-reversible dynamics with skew-symmetric matrices
F Futami, T Iwata, N Ueda, I Sato
Entropy 23 (8), 993, 2021
72021
Expectation propagation for t-exponential family using q-algebra
F Futami, I Sato, M Sugiyama
In Proceedings of the 31st International Conference on Neural Information …, 2017
62017
Time-varying Gaussian Process Bandit Optimization with Non-constant Evaluation Time
H Imamura, N Charoenphakdee, F Futami, I Sato, J Honda, M Sugiyama
arXiv preprint arXiv:2003.04691, 2020
52020
Time-Independent Information-Theoretic Generalization Bounds for SGLD
F Futami, M Fujisawa
Advances in Neural Information Processing Systems 36, 2024
42024
Loss function based second-order Jensen inequality and its application to particle variational inference
F Futami, T Iwata, I Sato, M Sugiyama
Advances in Neural Information Processing Systems 34, 6803-6815, 2021
42021
Information-theoretic analysis of test data sensitivity in uncertainty
F Futami, T Iwata
arXiv preprint arXiv:2307.12456, 2023
22023
Predictive variational Bayesian inference as risk-seeking optimization
F Futami, T Iwata, N Ueda, I Sato, M Sugiyama
International Conference on Artificial Intelligence and Statistics, 5051-5083, 2022
22022
Excess risk analysis for epistemic uncertainty with application to variational inference
F Futami, T Iwata, N Ueda, I Sato, M Sugiyama
arXiv preprint arXiv:2206.01606, 2022
12022
Information-theoretic Generalization Analysis for Expected Calibration Error
F Futami, M Fujisawa
arXiv preprint arXiv:2405.15709, 2024
2024
Information-theoretic Analysis of Bayesian Test Data Sensitivity
F Futami, T Iwata
International Conference on Artificial Intelligence and Statistics, 1099-1107, 2024
2024
Convergence of SVGD in KL divergence via approximate gradient flow
M Fujisawa, F Futami
2023
Scalable gradient matching based on state space Gaussian Processes
F Futami
Asian Conference on Machine Learning, 769-784, 2021
2021
Skew-symmetrically perturbed gradient flow for convex optimization
F Futami, T Iwata, N Ueda, I Yamane
Asian Conference on Machine Learning, 721-736, 2021
2021
Expectation Propagation for t-Exponential Family
F Futami, I Sato, M Sugiyama
IEICE Technical Report; IEICE Tech. Rep. 117 (110), 179-184, 2017
2017
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Articles 1–17