| Trainable ISTA for sparse signal recovery D Ito, S Takabe, T Wadayama IEEE Transactions on Signal Processing, 2019 | 260 | 2019 |
| Trainable projected gradient detector for massive overloaded MIMO channels: Data-driven tuning approach S Takabe, M Imanishi, T Wadayama, R Hayakawa, K Hayashi IEEE Access 7, 93326-93338, 2019 | 97 | 2019 |
| Deep learning-aided projected gradient detector for massive overloaded MIMO channels S Takabe, M Imanishi, T Wadayama, K Hayashi ICC 2019-2019 IEEE International Conference on Communications (ICC), 1-6, 2019 | 44 | 2019 |
| Deep learning-aided trainable projected gradient decoding for LDPC codes T Wadayama, S Takabe 2019 IEEE International Symposium on Information Theory (ISIT), 2444-2448, 2019 | 31 | 2019 |
| Chebyshev periodical successive over-relaxation for accelerating fixed-point iterations T Wadayama, S Takabe IEEE Signal Processing Letters 28, 907-911, 2021 | 29 | 2021 |
| Convergence acceleration via Chebyshev step: Plausible interpretation of deep-unfolded gradient descent S Takabe, T Wadayama IEICE Transactions on Fundamentals of Electronics, Communications and …, 2022 | 20 | 2022 |
| Complex trainable ISTA for linear and nonlinear inverse problems S Takabe, T Wadayama, YC Eldar ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 18 | 2020 |
| Fault Tolerance of Random Graphs with respect to Connectivity: Mean-field Approximation for Semi-dense Random Graphs S Takabe, T Nakano, T Wadayama arXiv preprint arXiv:1712.07807, 2017 | 15* | 2017 |
| Minimum vertex cover problems on random hypergraphs: replica symmetric solution and a leaf removal algorithm S Takabe, K Hukushima Physical Review E 89 (6), 062139, 2014 | 14 | 2014 |
| Deep unfolded multicast beamforming S Takabe, T Wadayama GLOBECOM 2020-2020 IEEE Global Communications Conference, 1-6, 2020 | 13 | 2020 |
| Theoretical interpretation of learned step size in deep-unfolded gradient descent S Takabe, T Wadayama arXiv preprint arXiv:2001.05142, 2020 | 12 | 2020 |
| Approximation theory for connectivity of ad hoc wireless networks with node faults S Takabe, T Wadayama IEEE Wireless Communications Letters 8 (4), 1240-1243, 2019 | 10 | 2019 |
| Deep learning-aided iterative detector for massive overloaded MIMO channels M Imanishi, S Takabe, T Wadayama arXiv preprint arXiv:1806.10827, 2018 | 10 | 2018 |
| Complex field-trainable ISTA for linear and nonlinear inverse problems S Takabe, T Wadayama | 9 | 2019 |
| Typical behavior of the linear programming method for combinatorial optimization problems: A statistical–mechanical perspective S Takabe, K Hukushima Journal of the Physical Society of Japan 83 (4), 043801, 2014 | 9 | 2014 |
| Asymptotic behavior of spatial coupling LDPC coding for compute-and-forward two-way relaying S Takabe, T Wadayama, M Hayashi IEEE Transactions on Communications 68 (7), 4063-4072, 2020 | 8 | 2020 |
| Asymptotic Analysis on Spatial Coupling Coding for Two-Way Relay Channels S Takabe, Y Ishimatsu, T Wadayama, M Hayashi arXiv preprint arXiv:1801.06328, 2018 | 7 | 2018 |
| Typical Performance of Approximation Algorithms for NP-hard Problems S Takabe, K Hukushima Journal of Statistical Mechanics: Theory and Experiment 2016, 113401, 2016 | 7 | 2016 |
| Convergence Acceleration of Markov Chain Monte Carlo-Based Gradient Descent by Deep Unfolding R Hagiwara, S Takabe Journal of the Physical Society of Japan 93 (6), 063801, 2024 | 6 | 2024 |
| Proximal decoding for LDPC codes T Wadayama, S Takabe IEICE Transactions on Fundamentals of Electronics, Communications and …, 2023 | 6 | 2023 |
Tadashi WadayamaNagoya Institute of TechnologyVerified email at nitech.ac.jp
