Akiyoshi Sannai

According to our database1, Akiyoshi Sannai authored at least 22 papers between 2018 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2025
LeanConjecturer: Automatic Generation of Mathematical Conjectures for Theorem Proving.
CoRR, June, 2025

Prover Agent: An Agent-based Framework for Formal Mathematical Proofs.
CoRR, June, 2025

Integrating Large Language Models in Causal Discovery: A Statistical Causal Approach.
Trans. Mach. Learn. Res., 2025

Bézier Flow: a Surface-wise Gradient Descent Method for Multi-objective Optimization.
Trans. Mach. Learn. Res., 2025

Stochastic Gradient Descent for Bézier Simplex Representation of Pareto Set in Multi-Objective Optimization.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2024
Universal approximation with neural networks on function spaces.
J. Exp. Theor. Artif. Intell., October, 2024

Decomposition of Equivariant Maps via Invariant Maps: Application to Universal Approximation under Symmetry.
Trans. Mach. Learn. Res., 2024

Invariant and Equivariant Reynolds Networks.
J. Mach. Learn. Res., 2024

Unification of Symmetries Inside Neural Networks: Transformer, Feedforward and Neural ODE.
CoRR, 2024

A Policy Gradient Primal-Dual Algorithm for Constrained MDPs with Uniform PAC Guarantees.
CoRR, 2024

2023
LPML: LLM-Prompting Markup Language for Mathematical Reasoning.
CoRR, 2023

2021
Equivariant and Invariant Reynolds Networks.
CoRR, 2021

Approximate Bayesian Computation of Bézier Simplices.
CoRR, 2021

Improved generalization bounds of group invariant / equivariant deep networks via quotient feature spaces.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Group Equivariant Conditional Neural Processes.
Proceedings of the 9th International Conference on Learning Representations, 2021

On the number of linear functions composing deep neural network: Towards a refined definition of neural networks complexity.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Universal Approximation Theorem for Equivariant Maps by Group CNNs.
CoRR, 2020

Asymptotic Risk of Bézier Simplex Fitting.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Improved Generalization Bound of Permutation Invariant Deep Neural Networks.
CoRR, 2019

Universal approximations of permutation invariant/equivariant functions by deep neural networks.
CoRR, 2019

Bézier Simplex Fitting: Describing Pareto Fronts of Simplicial Problems with Small Samples in Multi-Objective Optimization.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Reconstruction of training samples from loss functions.
CoRR, 2018


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