Akiyoshi Sannai

31 papers A* 3A 3Journal 25

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	SPECA: Specification-to-Checklist Agentic Auditing for Multi-Implementation Systems - A Case Study on Ethereum Clients. CoRR Masato Kamba, Akiyoshi Sannai
2025	J	`jnl`	Bézier Flow: a Surface-wise Gradient Descent Method for Multi-objective Optimization. Trans. Mach. Learn. Res. Akiyoshi Sannai, Yasunari Hikima, Ken Kobayashi, Akinori Tanaka, Naoki Hamada
2025	J	`jnl`	Discovering New Theorems via LLMs with In-Context Proof Learning in Lean. CoRR Kazumi Kasaura, Naoto Onda, Yuta Oriike, Masaya Taniguchi, Akiyoshi Sannai, Sho Sonoda
2025	J	`jnl`	Integrating Large Language Models in Causal Discovery: A Statistical Causal Approach. Trans. Mach. Learn. Res. Masayuki Takayama, Tadahisa Okuda, Thong Pham, Tatsuyoshi Ikenoue, Shingo Fukuma, Shohei Shimizu, Akiyoshi Sannai
2025	J	`jnl`	LeanConjecturer: Automatic Generation of Mathematical Conjectures for Theorem Proving. CoRR Naoto Onda, Kazumi Kasaura, Yuta Oriike, Masaya Taniguchi, Akiyoshi Sannai, Sho Sonoda
2025	J	`jnl`	Prover Agent: An Agent-based Framework for Formal Mathematical Proofs. CoRR Kaito Baba, Chaoran Liu, Shuhei Kurita, Akiyoshi Sannai
2025	A	`conf`	Stochastic Gradient Descent for Bézier Simplex Representation of Pareto Set in Multi-Objective Optimization. AISTATS Yasunari Hikima, Ken Kobayashi, Akinori Tanaka, Akiyoshi Sannai, Naoki Hamada
2024	J	`jnl`	A Policy Gradient Primal-Dual Algorithm for Constrained MDPs with Uniform PAC Guarantees. CoRR Toshinori Kitamura, Tadashi Kozuno, Masahiro Kato, Yuki Ichihara, Soichiro Nishimori, Akiyoshi Sannai, Sho Sonoda, Wataru Kumagai, Yutaka Matsuo
2024	J	`jnl`	Decomposition of Equivariant Maps via Invariant Maps: Application to Universal Approximation under Symmetry. CoRR Akiyoshi Sannai, Yuuki Takai, Matthieu Cordonnier
2024	J	`jnl`	Decomposition of Equivariant Maps via Invariant Maps: Application to Universal Approximation under Symmetry. Trans. Mach. Learn. Res. Akiyoshi Sannai, Yuuki Takai, Matthieu Cordonnier
2024	J	`jnl`	Integrating Large Language Models in Causal Discovery: A Statistical Causal Approach. CoRR Masayuki Takayama, Tadahisa Okuda, Thong Pham, Tatsuyoshi Ikenoue, Shingo Fukuma, Shohei Shimizu, Akiyoshi Sannai
2024	J	`jnl`	Invariant and Equivariant Reynolds Networks. J. Mach. Learn. Res. Akiyoshi Sannai, Makoto Kawano, Wataru Kumagai
2024	J	`jnl`	Unification of Symmetries Inside Neural Networks: Transformer, Feedforward and Neural ODE. CoRR Koji Hashimoto, Yuji Hirono, Akiyoshi Sannai
2024	J	`jnl`	Unification of symmetries inside neural networks: transformer, feedforward and neural ODE. Mach. Learn. Sci. Technol. Koji Hashimoto, Yuji Hirono, Akiyoshi Sannai
2024	J	`jnl`	Universal approximation with neural networks on function spaces. J. Exp. Theor. Artif. Intell. Wataru Kumagai, Akiyoshi Sannai, Makoto Kawano
2023	J	`jnl`	LPML: LLM-Prompting Markup Language for Mathematical Reasoning. CoRR Ryutaro Yamauchi, Sho Sonoda, Akiyoshi Sannai, Wataru Kumagai
2022	J	`jnl`	Bézier Flow: a Surface-wise Gradient Descent Method for Multi-objective Optimization. CoRR Akiyoshi Sannai, Yasunari Hikima, Ken Kobayashi, Akinori Tanaka, Naoki Hamada
2021	J	`jnl`	Approximate Bayesian Computation of Bézier Simplices. CoRR Akinori Tanaka, Akiyoshi Sannai, Ken Kobayashi, Naoki Hamada
2021	J	`jnl`	Equivariant and Invariant Reynolds Networks. CoRR Akiyoshi Sannai, Makoto Kawano, Wataru Kumagai
2021	A*	`conf`	Group Equivariant Conditional Neural Processes. ICLR Makoto Kawano, Wataru Kumagai, Akiyoshi Sannai, Yusuke Iwasawa, Yutaka Matsuo
2021	J	`jnl`	Group Equivariant Conditional Neural Processes. CoRR Makoto Kawano, Wataru Kumagai, Akiyoshi Sannai, Yusuke Iwasawa, Yutaka Matsuo
2021	A	`conf`	Improved generalization bounds of group invariant / equivariant deep networks via quotient feature spaces. UAI Akiyoshi Sannai, Masaaki Imaizumi, Makoto Kawano
2021	A	`conf`	On the number of linear functions composing deep neural network: Towards a refined definition of neural networks complexity. AISTATS Yuuki Takai, Akiyoshi Sannai, Matthieu Cordonnier
2020	A*	`conf`	Asymptotic Risk of Bézier Simplex Fitting. AAAI Akinori Tanaka, Akiyoshi Sannai, Ken Kobayashi, Naoki Hamada
2020	J	`jnl`	On the Number of Linear Functions Composing Deep Neural Network: Towards a Refined Definition of Neural Networks Complexity. CoRR Yuuki Takai, Akiyoshi Sannai, Matthieu Cordonnier
2020	J	`jnl`	Universal Approximation Theorem for Equivariant Maps by Group CNNs. CoRR Wataru Kumagai, Akiyoshi Sannai
2019	J	`jnl`	Asymptotic Risk of Bezier Simplex Fitting. CoRR Akinori Tanaka, Akiyoshi Sannai, Ken Kobayashi, Naoki Hamada
2019	A*	`conf`	Bézier Simplex Fitting: Describing Pareto Fronts of Simplicial Problems with Small Samples in Multi-Objective Optimization. AAAI Ken Kobayashi, Naoki Hamada, Akiyoshi Sannai, Akinori Tanaka, Kenichi Bannai, Masashi Sugiyama
2019	J	`jnl`	Improved Generalization Bound of Permutation Invariant Deep Neural Networks. CoRR Akiyoshi Sannai, Masaaki Imaizumi
2019	J	`jnl`	Universal approximations of permutation invariant/equivariant functions by deep neural networks. CoRR Akiyoshi Sannai, Yuuki Takai, Matthieu Cordonnier
2018	J	`jnl`	Reconstruction of training samples from loss functions. CoRR Akiyoshi Sannai