Takashi Furuya

29 papers A* 4A 1C 1Journal 22Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Approximation Theory for Lipschitz Continuous Transformers. CoRR Takashi Furuya, Davide Murari, Carola-Bibiane Schönlieb
2026	J	`jnl`	Approximation rates in Besov norms and sample-complexity of Kolmogorov-Arnold networks with residual connections. Neural Networks Anastasis Kratsios, Bum Jun Kim, Takashi Furuya
2025	J	`jnl`	Approximation Rates and VC-Dimension Bounds for (P)ReLU MLP Mixture of Experts. Trans. Mach. Learn. Res. Anastasis Kratsios, Haitz Sáez de Ocáriz Borde, Takashi Furuya, Marc T. Law
2025	J	`jnl`	Approximation theory for 1-Lipschitz ResNets. CoRR Davide Murari, Takashi Furuya, Carola-Bibiane Schönlieb
2025	J	`jnl`	Is In-Context Universality Enough? MLPs are Also Universal In-Context. CoRR Anastasis Kratsios, Takashi Furuya
2025	J	`jnl`	Kolmogorov-Arnold Networks: Approximation and Learning Guarantees for Functions and their Derivatives. CoRR Anastasis Kratsios, Takashi Furuya
2025	J	`jnl`	One model to solve them all: 2BSDE families via neural operators. CoRR Takashi Furuya, Anastasis Kratsios, Dylan Possamaï, Bogdan Raonic
2025	A*	`conf`	Quantitative Approximation for Neural Operators in Nonlinear Parabolic Equations. ICLR Takashi Furuya, Koichi Taniguchi, Satoshi Okuda
2025	A*	`conf`	Transformers are Universal In-context Learners. ICLR Takashi Furuya, Maarten V. de Hoop, Gabriel Peyré
2025	J	`jnl`	Transformers through the lens of support-preserving maps between measures. CoRR Takashi Furuya, Maarten V. de Hoop, Matti Lassas
2024	J	`jnl`	Breaking the Curse of Dimensionality with Distributed Neural Computation. CoRR Haitz Sáez de Ocáriz Borde, Takashi Furuya, Anastasis Kratsios, Marc T. Law
2024	A*	`conf`	Can neural operators always be continuously discretized? NeurIPS Takashi Furuya, Michael Puthawala, Matti Lassas, Maarten V. de Hoop
2024	J	`jnl`	Can neural operators always be continuously discretized? CoRR Takashi Furuya, Michael Puthawala, Maarten V. de Hoop, Matti Lassas
2024	J	`jnl`	Convergences for Minimax Optimization Problems over Infinite-Dimensional Spaces Towards Stability in Adversarial Training. Trans. Mach. Learn. Res. Takashi Furuya, Satoshi Okuda, Kazuma Suetake, Yoshihide Sawada
2024	J	`jnl`	Mixture of Experts Soften the Curse of Dimensionality in Operator Learning. CoRR Anastasis Kratsios, Takashi Furuya, Jose Antonio Lara Benitez, Matti Lassas, Maarten V. de Hoop
2024	J	`jnl`	Out-of-distributional risk bounds for neural operators with applications to the Helmholtz equation. J. Comput. Phys. Jose Antonio Lara Benitez, Takashi Furuya, Florian Faucher, Anastasis Kratsios, Xavier Tricoche, Maarten V. de Hoop
2024	J	`jnl`	Quantitative Approximation for Neural Operators in Nonlinear Parabolic Equations. CoRR Takashi Furuya, Koichi Taniguchi, Satoshi Okuda
2024	J	`jnl`	Simultaneously Solving FBSDEs with Neural Operators of Logarithmic Depth, Constant Width, and Sub-Linear Rank. CoRR Takashi Furuya, Anastasis Kratsios
2024	J	`jnl`	Transformers are Universal In-context Learners. CoRR Takashi Furuya, Maarten V. de Hoop, Gabriel Peyré
2023	J	`jnl`	Convergences for Minimax Optimization Problems over Infinite-Dimensional Spaces Towards Stability in Adversarial Training. CoRR Takashi Furuya, Satoshi Okuda, Kazuma Suetake, Yoshihide Sawada
2023	J	`jnl`	Fine-tuning Neural-Operator architectures for training and generalization. CoRR Jose Antonio Lara Benitez, Takashi Furuya, Florian Faucher, Xavier Tricoche, Maarten V. de Hoop
2023	A*	`conf`	Globally injective and bijective neural operators. NeurIPS Takashi Furuya, Michael Puthawala, Matti Lassas, Maarten V. de Hoop
2023	J	`jnl`	Globally injective and bijective neural operators. CoRR Takashi Furuya, Michael Puthawala, Matti Lassas, Maarten V. de Hoop
2022	C	`conf`	Assessment of Aqueduct Bridge Failure in Wakayama City, Japan, Based on Uav Surveying Flights and High-Resolution Sar Data. IGARSS Fumio Yamazaki, Wen Liu, Takashi Furuya, Yoshihisa Maruyama
2022	J	`jnl`	Inverse medium scattering problems with Kalman filter techniques. CoRR Takashi Furuya, Roland Potthast
2022	A	`conf`	Spectral Pruning for Recurrent Neural Networks. AISTATS Takashi Furuya, Kazuma Suetake, Koichi Taniguchi, Hiroyuki Kusumoto, Ryuji Saiin, Tomohiro Daimon
2022	J	`jnl`	Variational Inference with Gaussian Mixture by Entropy Approximation. CoRR Takashi Furuya, Hiroyuki Kusumoto, Koichi Taniguchi, Naoya Kanno, Kazuma Suetake
2021	J	`jnl`	Spectral Pruning for Recurrent Neural Networks. CoRR Takashi Furuya, Kazuma Suetake, Koichi Taniguchi, Hiroyuki Kusumoto, Ryuji Saiin, Tomohiro Daimon
2004	—	`conf`	Authoring augmented reality: a code-free approach. SIGGRAPH Posters Rodney Berry, Naoto Hikawa, Mao Makino, Masami Suzuki, Takashi Furuya