Faustino Gomez

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Juergen SchmidhuberKing Abdullah University of Science and Technology / The Swiss AI Lab, IDSIA / University of LuganoVerificeret mail på kaust.edu.sa
Risto MiikkulainenProfessor of Computer Science, the University of Texas at AustinVerificeret mail på cs.utexas.edu
Jan KoutníkDirector of Intelligent Automation, NNAISENSEVerificeret mail på idsia.ch
Alex GravesUniversity of TorontoVerificeret mail på cs.toronto.edu
Jonathan MasciNNAISENSE SAVerificeret mail på nnaisense.com
Giuseppe CuccuUniversity of FribourgVerificeret mail på unifr.ch
Santiago FernandezIK4-TeknikerVerificeret mail på tekniker.es
Yi SunGoogleVerificeret mail på idsia.ch
Rupesh Kumar SrivastavaNNAISENSEVerificeret mail på nnaisense.com
Matteo GaglioloAssociate Professor. GERME, Institute of Sociology, Université libre de Bruxelles, Brussels, BelgiumVerificeret mail på ulb.ac.be
Tom SchaulSenior Staff Scientist, DeepMindVerificeret mail på nyu.edu
Marijn StollengaIDSIA/Supsi, USIVerificeret mail på imfusion.com
Klaus GreffResearch Scientist at Google BrainVerificeret mail på usi.ch
Wojciech JaśkowskiSnowflakeVerificeret mail på snowflake.com
Julian TogeliusAssociate Professor of Computer Science and Engineering, New York University; co-founder, modl.aiVerificeret mail på nyu.edu
Marco GallieriSenior Data Scientist, DXT Commodities. Former F1 Engineer, Cambridge PhD.Verificeret mail på nnaisense.com
Mark RingIDSIAVerificeret mail på markring.com
Marco CicconePostdoctoral Fellow, Vector InstituteVerificeret mail på vectorinstitute.ai
Christian Osendorfer (Dr.)former TU MünchenVerificeret mail på in.tum.de
Doug BurgerCorporate VP, Managing Director, Microsoft Research CoreVerificeret mail på microsoft.com

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Faustino Gomez

CEO NNAISENSE SA. Former Senior Researcher, IDSIA, Switzerland

Verificeret mail på idsia.ch

AI Neural Networks Evolutionary Reinforcement Learning


Titel Sortér efter henvisninger Sortér efter årstal Sortér efter titel	Citeret af Citeret af	År
Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks A Graves, S Fernández, F Gomez, J Schmidhuber Proceedings of the 23rd International Conference on Machine Learning, 369-376, 2006	7463	2006
A Clockwork RNN J Koutnik, K Greff, F Gomez, J Schimdhuber International Conference on Machine Learning (ICML), 2014	716	2014
Incremental evolution of complex general behavior F Gomez, R Miikkulainen Adaptive Behavior 5 (3-4), 317-342, 1997	617	1997
Accelerated Neural Evolution through Cooperatively Coevolved Synapses. F Gomez, J Schmidhuber, R Miikkulainen Journal of Machine Learning Research 9 (5), 2008	402	2008
Solving non-Markovian control tasks with neuroevolution FJ Gomez, R Miikkulainen IJCAI 99, 1356-1361, 1999	355	1999
Training recurrent networks by evolino J Schmidhuber, D Wierstra, M Gagliolo, F Gomez Neural Computation 19 (3), 757-779, 2007	339	2007
Deep networks with internal selective attention through feedback connections MF Stollenga, J Masci, F Gomez, J Schmidhuber Advances in neural information processing systems 27, 2014	336	2014
A system for robotic heart surgery that learns to tie knots using recurrent neural networks H Mayer, F Gomez, D Wierstra, I Nagy, A Knoll, J Schmidhuber Advanced Robotics 22 (13-14), 1521-1537, 2008	305	2008
Evolving Large-Scale Neural Networks for Vision-Based Reinforcement Learning J Koutník, G Cuccu, J Schmidhuber, F Gomez Genetic and Evolutionary Computation Conference (GECCO), 2013	248	2013
Compete to compute RK Srivastava, J Masci, S Kazerounian, F Gomez, J Schmidhuber Advances in neural information processing systems 26, 2013	248	2013
Model-based active exploration P Shyam, W Jaśkowski, F Gomez International conference on machine learning, 5779-5788, 2019	234	2019
Robust non-linear control through neuroevolution FJ Gomez Computer Science Department, University of Texas, 2003	212	2003
Planning to be surprised: Optimal bayesian exploration in dynamic environments Y Sun, F Gomez, J Schmidhuber Artificial General Intelligence: 4th International Conference, AGI 2011 …, 2011	193	2011
Efficient non-linear control through neuroevolution F Gomez, J Schmidhuber, R Miikkulainen European Conference on Machine Learning, 654-662, 2006	183	2006
Active guidance for a finless rocket using neuroevolution F Gomez, R Miikkulainen International Conference on Genetic and Evolutionary Computation—GECCO 2003 …, 2003	177	2003
Evolving deep unsupervised convolutional networks for vision-based reinforcement learning J Koutník, J Schmidhuber, F Gomez Proceedings of the 2014 Annual Conference on Genetic and Evolutionary …, 2014	154	2014
Evolino: Hybrid neuroevolution/optimal linear search for sequence prediction J Schmidhuber, D Wierstra, FJ Gomez Proceedings of the 19th International Joint Conferenceon Artificial …, 2005	151	2005
When novelty is not enough G Cuccu, F Gomez Evostar 2011 (Turin), 234-243, 2011	132	2011
Co-evolving recurrent neurons learn deep memory POMDPs FJ Gomez, J Schmidhuber Proceedings of the 2005 Conference on Genetic and Evolutionary Computation …, 2005	111	2005
Evolving neural networks in compressed weight space J Koutník, F Gomez, J Schmidhuber Proceedings of the Conference on Genetic and Evolutionary Computation (GECCO-10), 2010	109	2010

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