| Trainable ISTA for sparse signal recovery D Ito, S Takabe, T Wadayama IEEE Transactions on Signal Processing 67 (12), 3113-3125, 2019 | 260 | 2019 |
| A typical reconstruction limit for compressed sensing based onLp-norm minimization Y Kabashima, T Wadayama, T Tanaka Journal of Statistical Mechanics: Theory and Experiment 2009 (09), L09003, 2009 | 217 | 2009 |
| Gradient descent bit flipping algorithms for decoding LDPC codes T Wadayama, K Nakamura, M Yagita, Y Funahashi, S Usami, I Takumi IEEE Transactions on Communications 58 (6), 1610-1614, 2010 | 216 | 2010 |
| 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 |
| Low-density parity-check matrices for coding of correlated sources J Muramatsu, T Uyematsu, T Wadayama IEEE Transactions on Information Theory 51 (10), 3645-3654, 2005 | 93 | 2005 |
| A coded modulation scheme based on low density parity check codes T Wadayama IEICE transactions on fundamentals of electronics, communications and …, 2001 | 63 | 2001 |
| Introduction to low density parity check codes and sum-product algorithm T Wadayama w/English translation of abstract thereof, Technical Report of IEICE, 1-8, 2001 | 57 | 2001 |
| Coded M-FSK for power line communications AJH Vinck, J Haering, T Wadayama 2000 IEEE International Symposium on Information Theory (Cat. No. 00CH37060 …, 2000 | 54 | 2000 |
| Gradient descent bit flipping algorithms for decoding LDPC codes T Wadayama, K Nakamura, M Yagita, Y Funahashi, S Usami, I Takumi 2008 International Symposium on Information Theory and Its Applications, 1-6, 2008 | 50 | 2008 |
| Interior point decoding for linear vector channels based on convex optimization T Wadayama IEEE transactions on information theory 56 (10), 4905-4921, 2010 | 49 | 2010 |
| Low density parity check matrices for coding of multiple access networks J Muramatsu, T Uyematsu, T Wadayama Proceedings 2003 IEEE Information Theory Workshop (Cat. No. 03EX674), 304-307, 2003 | 45 | 2003 |
| 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 |
| An analysis on non-adaptive group testing based on sparse pooling graphs T Wadayama 2013 IEEE International Symposium on Information Theory, 2681-2685, 2013 | 40* | 2013 |
| An iterative decoding algorithm of low density parity check codes for hidden Markov noise channels T Wadayama ISITA2000, Hawaii, Nov., 2000 | 35 | 2000 |
| LP-decodable permutation codes based on linearly constrained permutation matrices T Wadayama, M Hagiwara IEEE Transactions on Information Theory 58 (8), 5454-5470, 2012 | 33 | 2012 |
| 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 |
| Deep learning-based average consensus M Kishida, M Ogura, Y Yoshida, T Wadayama IEEE Access 8, 142404-142412, 2020 | 30 | 2020 |
| Chebyshev periodical successive over-relaxation for accelerating fixed-point iterations T Wadayama, S Takabe IEEE Signal Processing Letters 28, 907-911, 2021 | 29 | 2021 |
| A multilevel construction of permutation codes T Wadayama, H AJ IEICE transactions on fundamentals of electronics, communications and …, 2001 | 28 | 2001 |
| A cutting-plane method based on redundant rows for improving fractional distance M Miwa, T Wadayama, I Takumi IEEE Journal on Selected Areas in Communications 27 (6), 1005-1012, 2009 | 27 | 2009 |
