Pablo Sprechmann
Pablo Sprechmann
Research Scientist at Google DeepMind
Verified email at
Cited by
Cited by
Gemini: a family of highly capable multimodal models
G Team, R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, ...
arXiv preprint arXiv:2312.11805, 2023
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
Accelerating eulerian fluid simulation with convolutional networks
J Tompson, K Schlachter, P Sprechmann, K Perlin
International conference on machine learning, 3424-3433, 2017
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
Disentangling factors of variation in deep representation using adversarial training
MF Mathieu, JJ Zhao, J Zhao, A Ramesh, P Sprechmann, Y LeCun
Advances in neural information processing systems 29, 2016
Super-resolution with deep convolutional sufficient statistics
J Bruna, P Sprechmann, Y LeCun
arXiv preprint arXiv:1511.05666, 2015
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
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
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
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
Memory-based parameter adaptation
P Sprechmann, SM Jayakumar, JW Rae, A Pritzel, AP Badia, B Uria, ...
arXiv preprint arXiv:1802.10542, 2018
Game Plan: What AI can do for Football, and What Football can do for AI
K Tuyls, S Omidshafiei, P Muller, Z Wang, J Connor, D Hennes, I Graham, ...
Journal of Artificial Intelligence Research 71, 41-88, 2021
Meta-learning of sequential strategies
PA Ortega, JX Wang, M Rowland, T Genewein, Z Kurth-Nelson, ...
arXiv preprint arXiv:1905.03030, 2019
Supervised sparse analysis and synthesis operators
P Sprechmann, R Litman, T Ben Yakar, AM Bronstein, G Sapiro
Advances in Neural Information Processing Systems 26, 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
Quantifying risk for anxiety disorders in preschool children: a machine learning approach
KLH Carpenter, P Sprechmann, R Calderbank, G Sapiro, HL Egger
PloS one 11 (11), e0165524, 2016
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
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