Akiyoshi Sannai

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 19

Top Topics

Linear Functions

Markup Language

Top Venues

Publications

Koji Hashimoto, Yuji Hirono, Akiyoshi Sannai
Unification of Symmetries Inside Neural Networks: Transformer, Feedforward and Neural ODE. CoRR (2024)
Toshinori Kitamura, Tadashi Kozuno, Masahiro Kato, Yuki Ichihara, Soichiro Nishimori, Akiyoshi Sannai, Sho Sonoda, Wataru Kumagai, Yutaka Matsuo
A Policy Gradient Primal-Dual Algorithm for Constrained MDPs with Uniform PAC Guarantees. CoRR (2024)
Masayuki Takayama, Tadahisa Okuda, Thong Pham, Tatsuyoshi Ikenoue, Shingo Fukuma, Shohei Shimizu, Akiyoshi Sannai
Integrating Large Language Models in Causal Discovery: A Statistical Causal Approach. CoRR (2024)
Ryutaro Yamauchi, Sho Sonoda, Akiyoshi Sannai, Wataru Kumagai
LPML: LLM-Prompting Markup Language for Mathematical Reasoning. CoRR (2023)
Akiyoshi Sannai, Yasunari Hikima, Ken Kobayashi, Akinori Tanaka, Naoki Hamada
Bézier Flow: a Surface-wise Gradient Descent Method for Multi-objective Optimization. CoRR (2022)
Yuuki Takai, Akiyoshi Sannai, Matthieu Cordonnier
On the number of linear functions composing deep neural network: Towards a refined definition of neural networks complexity. AISTATS (2021)
Akinori Tanaka, Akiyoshi Sannai, Ken Kobayashi, Naoki Hamada
Approximate Bayesian Computation of Bézier Simplices. CoRR (2021)
Akiyoshi Sannai, Makoto Kawano, Wataru Kumagai
Equivariant and Invariant Reynolds Networks. CoRR (2021)
Makoto Kawano, Wataru Kumagai, Akiyoshi Sannai, Yusuke Iwasawa, Yutaka Matsuo
Group Equivariant Conditional Neural Processes. CoRR (2021)
Akiyoshi Sannai, Masaaki Imaizumi, Makoto Kawano
Improved generalization bounds of group invariant / equivariant deep networks via quotient feature spaces. UAI (2021)
Makoto Kawano, Wataru Kumagai, Akiyoshi Sannai, Yusuke Iwasawa, Yutaka Matsuo
Group Equivariant Conditional Neural Processes. ICLR (2021)
Akinori Tanaka, Akiyoshi Sannai, Ken Kobayashi, Naoki Hamada
Asymptotic Risk of Bézier Simplex Fitting. AAAI (2020)
Yuuki Takai, Akiyoshi Sannai, Matthieu Cordonnier
On the Number of Linear Functions Composing Deep Neural Network: Towards a Refined Definition of Neural Networks Complexity. CoRR (2020)
Wataru Kumagai, Akiyoshi Sannai
Universal Approximation Theorem for Equivariant Maps by Group CNNs. CoRR (2020)
Akinori Tanaka, Akiyoshi Sannai, Ken Kobayashi, Naoki Hamada
Asymptotic Risk of Bezier Simplex Fitting. CoRR (2019)
Akiyoshi Sannai, Masaaki Imaizumi
Improved Generalization Bound of Permutation Invariant Deep Neural Networks. CoRR (2019)
Ken Kobayashi, Naoki Hamada, Akiyoshi Sannai, Akinori Tanaka, Kenichi Bannai, Masashi Sugiyama
Bézier Simplex Fitting: Describing Pareto Fronts of Simplicial Problems with Small Samples in Multi-Objective Optimization. AAAI (2019)
Akiyoshi Sannai, Yuuki Takai, Matthieu Cordonnier
Universal approximations of permutation invariant/equivariant functions by deep neural networks. CoRR (2019)
Akiyoshi Sannai
Reconstruction of training samples from loss functions. CoRR (2018)