- Mohammadreza Soltaniyeh, Richard P. Martin, Santosh Nagarakatte:
Synergistic CPU-FPGA Acceleration of Sparse Linear Algebra. CoRR abs/2004.13907 (2020) - Minsu Cho, Mohammadreza Soltani, Chinmay Hegde:
Hyperparameter Optimization in Neural Networks via Structured Sparse Recovery. CoRR abs/2007.04087 (2020) - Chris Cannella, Mohammadreza Soltani, Vahid Tarokh:
Projected Latent Markov Chain Monte Carlo: Conditional Inference with Normalizing Flows. CoRR abs/2007.06140 (2020) - Robert J. Ravier, Mohammadreza Soltani, Miguel Antunes Dias Alfaiate, Denis Garagic, Vahid Tarokh:
An Interpretable Baseline for Time Series Classification Without Intensive Learning. CoRR abs/2007.06682 (2020) - Cat P. Le, Mohammadreza Soltani, Robert J. Ravier, Vahid Tarokh:
Task-Aware Neural Architecture Search. CoRR abs/2010.13962 (2020) - 2019
- Giuseppe Pica, Mohammadreza Soltanipour, Stefano Panzeri:
Using intersection information to map stimulus information transfer within neural networks. Biosyst. 185 (2019) - Mohammadreza Moradian, Jafar Soltani, Abbas Najjar-Khodabakhsh, Gholamreza Arab Markadeh:
Adaptive Torque and Flux Control of Sensorless IPMSM Drive in the Stator Flux Field Oriented Reference Frame. IEEE Trans. Ind. Informatics 15(1): 205-212 (2019) - Mohammadreza Soltani, Chinmay Hegde:
Fast and Provable Algorithms for Learning Two-Layer Polynomial Neural Networks. IEEE Trans. Signal Process. 67(13): 3361-3371 (2019) - Mohammadreza Soltani, Swayambhoo Jain, Abhinav V. Sambasivan, Chinmay Hegde:
Leaming Structured Signals Using GAN s with Applications in Denoising and Demixing. ACSSC 2019: 2127-2131 - Mehdi Amian, Mohammadreza Soltaninejad:
Multi-resolution 3D CNN for MRI Brain Tumor Segmentation and Survival Prediction. BrainLes@MICCAI (1) 2019: 221-230 - Mohammadreza Soltani, Swayambhoo Jain, Abhinav V. Sambasivan:
Unsupervised Demixing of Structured Signals from Their Superposition Using GANs. DGS@ICLR 2019 - Mohammadreza Soltani, Swayambhoo Jain, Abhinav V. Sambasivan:
Learning Generative Models of Structured Signals from Their Superposition Using GANs with Application to Denoising and Demixing. CoRR abs/1902.04664 (2019) - Minsu Cho, Mohammadreza Soltani, Chinmay Hegde:
One-Shot Neural Architecture Search via Compressive Sensing. CoRR abs/1906.02869 (2019) - Mohammadreza Soltaninejad, Lei Zhang, Tryphon Lambrou, Guang Yang, Nigel M. Allinson, Xujiong Ye:
MRI Brain Tumor Segmentation using Random Forests and Fully Convolutional Networks. CoRR abs/1909.06337 (2019) - Chris Cannella, Jie Ding, Mohammadreza Soltani, Vahid Tarokh:
Perception-Distortion Trade-off with Restricted Boltzmann Machines. CoRR abs/1910.09122 (2019) - Mehdi Amian, Mohammadreza Soltaninejad:
Multi-Resolution 3D CNN for MRI Brain Tumor Segmentation and Survival Prediction. CoRR abs/1911.08388 (2019) - 2018
- Mohammadreza Soltaninejad, Guang Yang, Tryphon Lambrou, Nigel M. Allinson, Timothy L. Jones, Thomas R. Barrick, Franklyn A. Howe, Xujiong Ye:
Supervised Learning based Multimodal MRI Brain Tumour Segmentation using Texture Features from Supervoxels#. Comput. Methods Programs Biomed. 157 (2018) - Sanaz Soltani, Mohammadreza Razzazi, Hossein Ghasemalizadeh:
The Most Points Connected-Covering Problem with Two Disks. Theory Comput. Syst. 62(8): 2035-2047 (2018) - Mohammadreza Soltaniyeh, Ismail Kadayif, Ozcan Ozturk:
Classifying Data Blocks at Subpage Granularity With an On-Chip Page Table to Improve Coherence in Tiled CMPs. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 37(4): 806-819 (2018) - Mohammadreza Soltani, Chinmay Hegde:
Towards Provable Learning of Polynomial Neural Networks Using Low-Rank Matrix Estimation. AISTATS 2018: 1417-1426 - Mohammadreza Soltani, Chinmay Hegde:
Fast Low-Rank Matrix Estimation for Ill-Conditioned Matrices. ISIT 2018: 371-375 - 2017
- Mohammadreza Soltaninejad:
Supervised learning-based multimodal MRI brain image analysis. University of Lincoln, UK, 2017 - Mohammadreza Soltaninejad, Guang Yang, Tryphon Lambrou, Nigel M. Allinson, Timothy L. Jones, Thomas R. Barrick, Franklyn A. Howe, Xujiong Ye:
Automated brain tumour detection and segmentation using superpixel-based extremely randomized trees in FLAIR MRI. Int. J. Comput. Assist. Radiol. Surg. 12(2): 183-203 (2017) - Mohammadreza Soltani, Chinmay Hegde:
Fast Algorithms for Demixing Sparse Signals From Nonlinear Observations. IEEE Trans. Signal Process. 65(16): 4209-4222 (2017) - Viraj Shah, Mohammadreza Soltani, Chinmay Hegde:
Reconstruction from periodic nonlinearities, with applications to HDR imaging. ACSSC 2017: 863-867 - Mohammadreza Soltani, Chinmay Hegde:
Demixing structured superposition signals from periodic and aperiodic nonlinear observations. GlobalSIP 2017: 1165-1169 - Mohammadreza Soltani, Chinmay Hegde:
Stable recovery of sparse vectors from random sinusoidal feature maps. ICASSP 2017: 6384-6388 - Mohammadreza Soltaninejad, Lei Zhang, Tryphon Lambrou, Guang Yang, Nigel M. Allinson, Xujiong Ye:
MRI Brain Tumor Segmentation and Patient Survival Prediction Using Random Forests and Fully Convolutional Networks. BrainLes@MICCAI 2017: 204-215 - Mohammadreza Soltaninejad, Lei Zhang, Tryphon Lambrou, Nigel M. Allinson, Xujiong Ye:
Multimodal MRI brain tumor segmentation using random forests with features learned from fully convolutional neural network. CoRR abs/1704.08134 (2017) - 2016
- Mohammadreza Soltani, Chinmay Hegde:
Demixing sparse signals from nonlinear observations. ACSSC 2016: 615-619