Pablo Sprechmann
Pablo Sprechmann
Research Scientist at Google DeepMind
Verified email at
Cited by
Cited by
Classification and clustering via dictionary learning with structured incoherence and shared features
I Ramirez, P Sprechmann, G Sapiro
Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on …, 2010
Disentangling factors of variation in deep representations using adversarial training
M Mathieu, J Zhao, P Sprechmann, A Ramesh, Y LeCun
arXiv preprint arXiv:1611.03383, 2016
Accelerating eulerian fluid simulation with convolutional networks
J Tompson, K Schlachter, P Sprechmann, K Perlin
International Conference on Machine Learning, 3424-3433, 2017
Super-resolution with deep convolutional sufficient statistics
J Bruna, P Sprechmann, Y LeCun
arXiv preprint arXiv:1511.05666, 2015
C-HiLasso: A Collaborative Hierarchical Sparse Modeling Framework
P Sprechmann, I Ramírez, G Sapiro, YC Eldar
Signal Processing, IEEE Transactions on 59 (9), 4183-4198, 2011
Learning efficient sparse and low rank models
P Sprechmann, AM Bronstein, G Sapiro
IEEE transactions on pattern analysis and machine intelligence 37 (9), 1821-1833, 2015
Agent57: Outperforming the atari human benchmark
AP Badia, B Piot, S Kapturowski, P Sprechmann, A Vitvitskyi, ZD Guo, ...
International Conference on Machine Learning, 507-517, 2020
Classification and 3D averaging with missing wedge correction in biological electron tomography
A Bartesaghi, P Sprechmann, J Liu, G Randall, G Sapiro, S Subramaniam
Journal of structural biology 162 (3), 436-450, 2008
Dictionary learning and sparse coding for unsupervised clustering
P Sprechmann, G Sapiro
2010 IEEE international conference on acoustics, speech and signal …, 2010
Sparse modeling of intrinsic correspondences
J Pokrass, AM Bronstein, MM Bronstein, P Sprechmann, G Sapiro
Computer Graphics Forum 32 (2pt4), 459-468, 2013
Real-time Online Singing Voice Separation from Monaural Recordings Using Robust Low-rank Modeling.
P Sprechmann, AM Bronstein, G Sapiro
ISMIR, 67-72, 2012
Memory-based parameter adaptation
P Sprechmann, SM Jayakumar, JW Rae, A Pritzel, AP Badia, B Uria, ...
arXiv preprint arXiv:1802.10542, 2018
Never give up: Learning directed exploration strategies
A Puigdomènech Badia, P Sprechmann, A Vitvitskyi, D Guo, B Piot, ...
arXiv e-prints, arXiv: 2002.06038, 2020
Supervised sparse analysis and synthesis operators
P Sprechmann, R Litman, T Ben Yakar, AM Bronstein, G Sapiro
Advances in Neural Information Processing Systems 26, 908-916, 2013
Collaborative hierarchical sparse modeling
P Sprechmann, I Ramirez, G Sapiro, Y Eldar
2010 44th Annual Conference on Information Sciences and Systems (CISS), 1-6, 2010
Supervised non-euclidean sparse NMF via bilevel optimization with applications to speech enhancement
P Sprechmann, AM Bronstein, G Sapiro
2014 4th Joint Workshop on Hands-free Speech Communication and Microphone …, 2014
Learning efficient structured sparse models
A Bronstein, P Sprechmann, G Sapiro
arXiv preprint arXiv:1206.4649, 2012
Robust multimodal graph matching: Sparse coding meets graph matching
M Fiori, P Sprechmann, J Vogelstein, P Musé, G Sapiro
arXiv preprint arXiv:1311.6425, 2013
Meta-learning of sequential strategies
PA Ortega, JX Wang, M Rowland, T Genewein, Z Kurth-Nelson, ...
arXiv preprint arXiv:1905.03030, 2019
Meta-learning by the baldwin effect
C Fernando, J Sygnowski, S Osindero, J Wang, T Schaul, D Teplyashin, ...
Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2018
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