SPIRAL: Code generation for DSP transforms M Püschel, JMF Moura, JR Johnson, D Padua, MM Veloso, BW Singer, ... Proceedings of the IEEE 93 (2), 232-275, 2005 | 1070 | 2005 |
An abstract domain for certifying neural networks G Singh, T Gehr, M Püschel, M Vechev Proceedings of the ACM on Programming Languages 3 (POPL), 1-30, 2019 | 753 | 2019 |
Fast and effective robustness certification G Singh, T Gehr, M Mirman, M Püschel, M Vechev Advances in neural information processing systems 31, 2018 | 561 | 2018 |
Multiplierless multiple constant multiplication Y Voronenko, M Püschel ACM Transactions on Algorithms (TALG) 3 (2), 11-es, 2007 | 560 | 2007 |
D-ADMM: A communication-efficient distributed algorithm for separable optimization JFC Mota, JMF Xavier, PMQ Aguiar, M Püschel IEEE Transactions on Signal Processing 61 (10), 2718-2723, 2013 | 436 | 2013 |
Spiral: A generator for platform-adapted libraries of signal processing algorithms M Püschel, JMF Moura, B Singer, JX Xiong, J Johnson, D Padua, ... International Journal of High Performance Computing Applications 18 (2), 279-279, 2004 | 274 | 2004 |
Distributed basis pursuit JFC Mota, JMF Xavier, PMQ Aguiar, M Püschel IEEE Transactions on Signal Processing 60 (4), 1942-1956, 2012 | 242 | 2012 |
Boosting robustness certification of neural networks G Singh, T Gehr, M Püschel, M Vechev International Conference on Learning Representations, 2019 | 209 | 2019 |
Beyond the single neuron convex barrier for neural network certification G Singh, R Ganvir, M Püschel, M Vechev Advances in Neural Information Processing Systems, 15072-15083, 2019 | 204 | 2019 |
Active learning for multi-objective optimization M Zuluaga, A Krause, G Sergent, M Püschel International Conference on Machine Learning 28, 462-470, 2013 | 203 | 2013 |
Algebraic signal processing theory: Foundation and 1-D time M Püschel, JMF Moura IEEE Transactions on Signal Processing 56 (8), 3572-3585, 2008 | 199 | 2008 |
Computer generation of hardware for linear digital signal processing transforms P Milder, F Franchetti, JC Hoe, M Püschel ACM Transactions on Design Automation of Electronic Systems (TODAES) 17 (2 …, 2012 | 156 | 2012 |
Applying the roofline model G Ofenbeck, R Steinmann, V Caparros, DG Spampinato, M Püschel Performance Analysis of Systems and Software (ISPASS), 2014 IEEE …, 2014 | 149 | 2014 |
The algebraic approach to the discrete cosine and sine transforms and their fast algorithms M Püschel, JMF Moura SIAM Journal on Computing 32 (5), 1280-1316, 2003 | 144 | 2003 |
Algebraic signal processing theory: 1-D space M Püschel, JMF Moura IEEE Transactions on Signal Processing 56 (8), 3586-3599, 2008 | 132 | 2008 |
Algebraic signal processing theory: Cooley–Tukey type algorithms for DCTs and DSTs M Püschel, JMF Moura IEEE Transactions on Signal Processing 56 (4), 1502-1521, 2008 | 130 | 2008 |
Fast polyhedra abstract domain G Singh, M Püschel, M Vechev Proceedings of the 44th ACM SIGPLAN Symposium on Principles of Programming …, 2017 | 127 | 2017 |
Discrete Fourier transform on multicore F Franchetti, M Püschel, Y Voronenko, S Chellappa, JMF Moura IEEE Signal Processing Magazine 26 (6), 90-102, 2009 | 123 | 2009 |
SPIRAL: Extreme performance portability F Franchetti, TM Low, DT Popovici, RM Veras, DG Spampinato, ... Proceedings of the IEEE 106 (11), 1935-1968, 2018 | 120 | 2018 |
ε-Pal: An active learning approach to the multi-objective optimization problem M Zuluaga, A Krause, M Püschel The Journal of Machine Learning Research 17 (1), 3619-3650, 2016 | 120* | 2016 |