| Deep learning for stock prediction using numerical and textual information R Akita, A Yoshihara, T Matsubara, K Uehara 2016 IEEE/ACIS 15th International Conference on Computer and Information …, 2016 | 480 | 2016 |
| Data augmentation using random image cropping and patching for deep CNNs R Takahashi, T Matsubara, K Uehara IEEE Transactions on Circuits and Systems for Video Technology 30 (9), 2917-2931, 2019 | 451 | 2019 |
| RICAP: Random image cropping and patching data augmentation for deep cnns R Takahashi, T Matsubara, K Uehara Asian conference on machine learning, 786-798, 2018 | 149 | 2018 |
| Classification and characterisation of brain network changes in chronic back pain: A multicenter study. Wellcome Open Res. 2018; 3: 19 H Mano, G Kotecha, K Leibnitz, T Matsubara, A Nakae, N Shenker | 83* | |
| Asynchronous cellular automaton-based neuron: theoretical analysis and on-FPGA learning T Matsubara, H Torikai IEEE transactions on neural networks and learning systems 24 (5), 736-748, 2013 | 67 | 2013 |
| A generalized rotate-and-fire digital spiking neuron model and its on-FPGA learning T Matsubara, H Torikai, T Hishiki IEEE Transactions on Circuits and Systems II: Express Briefs 58 (10), 677-681, 2011 | 66 | 2011 |
| An asynchronous recurrent network of cellular automaton-based neurons and its reproduction of spiking neural network activities T Matsubara, H Torikai IEEE Transactions on Neural Networks and Learning Systems 27 (4), 836-852, 2015 | 63 | 2015 |
| Stock price prediction by deep neural generative model of news articles T Matsubara, R Akita, K Uehara IEICE TRANSACTIONS on Information and Systems 101 (4), 901-908, 2018 | 61 | 2018 |
| Deep Energy-Based Modeling of Discrete-Time Physics T Matsubara, A Ishikawa, T Yaguchi Advances in Neural Information Processing Systems 33, 2020 | 55 | 2020 |
| Deep neural generative model of functional MRI images for psychiatric disorder diagnosis T Matsubara, T Tashiro, K Uehara IEEE Transactions on Biomedical Engineering 66 (10), 2768-2779, 2019 | 48 | 2019 |
| Image generation using generative adversarial networks and attention mechanism Y Kataoka, T Matsubara, K Uehara 2016 IEEE/ACIS 15th International Conference on Computer and Information …, 2016 | 47 | 2016 |
| Neural symplectic form: Learning Hamiltonian equations on general coordinate systems Y Chen, T Matsubara, T Yaguchi Advances in Neural Information Processing Systems 34, 16659-16670, 2021 | 40 | 2021 |
| Deep generative model using unregularized score for anomaly detection with heterogeneous complexity T Matsubara, K Sato, K Hama, R Tachibana, K Uehara IEEE Transactions on Cybernetics 52 (6), 5161-5173, 2020 | 32 | 2020 |
| A novel weight-shared multi-stage CNN for scale robustness R Takahashi, T Matsubara, K Uehara IEEE Transactions on Circuits and Systems for Video Technology 29 (4), 1090-1101, 2018 | 29 | 2018 |
| Symplectic adjoint method for exact gradient of neural ODE with minimal memory T Matsubara, Y Miyatake, T Yaguchi Advances in Neural Information Processing Systems 34, 20772-20784, 2021 | 26 | 2021 |
| Guidelines for creating artificial neural network empirical interatomic potential from first-principles molecular dynamics data under specific conditions and its application to … K Shimamura, S Fukushima, A Koura, F Shimojo, M Misawa, RK Kalia, ... The Journal of Chemical Physics 151 (12), 2019 | 24 | 2019 |
| Generative adversarial network based on chaotic time series M Naruse, T Matsubara, N Chauvet, K Kanno, T Yang, A Uchida Scientific reports 9 (1), 12963, 2019 | 24 | 2019 |
| Hypernetwork-based implicit posterior estimation and model averaging of cnn K Ukai, T Matsubara, K Uehara Asian conference on machine learning, 176-191, 2018 | 21 | 2018 |
| Anomaly machine component detection by deep generative model with unregularized score T Matsubara, R Tachibana, K Uehara 2018 International Joint Conference on Neural Networks (IJCNN), 1-8, 2018 | 21 | 2018 |
| Predictable uncertainty-aware unsupervised deep anomaly segmentation K Sato, K Hama, T Matsubara, K Uehara 2019 international joint conference on neural networks (ijcnn), 1-7, 2019 | 16 | 2019 |
