Faustino J. Gomez

发表

Sustaining diversity using behavioral information distance

Faustino J. Gomez, F. Gomez, 2009, GECCO.

Generalized compressed network search

Jürgen Schmidhuber, Faustino J. Gomez, Rupesh Kumar Srivastava, 2012, GECCO '12.

A System for Robotic Heart Surgery that Learns to Tie Knots Using Recurrent Neural Networks

Jürgen Schmidhuber, Alois Knoll, Faustino J. Gomez, 2006 .

Online Evolution of Deep Convolutional Network for Vision-Based Reinforcement Learning

Jürgen Schmidhuber, Jan Koutník, Faustino J. Gomez, 2014, SAB.

Training Recurrent Networks by Evolino

Jürgen Schmidhuber, Faustino J. Gomez, Daan Wierstra, 2007, Neural Computation.

Co-evolving recurrent neurons learn deep memory POMDPs

Jürgen Schmidhuber, Faustino J. Gomez, J. Schmidhuber, 2005, GECCO '05.

Evolving large-scale neural networks for vision-based reinforcement learning

Jürgen Schmidhuber, Jan Koutník, Faustino J. Gomez, 2013, GECCO '13.

Evolving Modular Fast-Weight Networks for Control

Jürgen Schmidhuber, Faustino J. Gomez, J. Schmidhuber, 2005, ICANN.

Novelty-based restarts for evolution strategies

Faustino J. Gomez, Giuseppe Cuccu, Tobias Glasmachers, 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).

On the Size of the Online Kernel Sparsification Dictionary pdf

Yi Sun, Jürgen Schmidhuber, Faustino J. Gomez, 2012, ICML.

Modeling systems with internal state using evolino

Jürgen Schmidhuber, Faustino J. Gomez, Daan Wierstra, 2005, GECCO '05.

Metric State Space Reinforcement Learning for a Vision-Capable Mobile Robot pdf

Jürgen Schmidhuber, Marcus Hutter, Faustino J. Gomez, 2006, IAS.

Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks

Jürgen Schmidhuber, Alex Graves, Santiago Fernández, 2006, ICML.

Rapid Humanoid Motion Learning through Coordinated, Parallel Evolution

Jürgen Schmidhuber, Marijn F. Stollenga, Faustino J. Gomez, 2014, SAB.

Solving Non-Markovian Control Tasks with Neuro-Evolution

Risto Miikkulainen, Faustino J. Gomez, R. Miikkulainen, 1999, IJCAI.

A reinforcement learning approach for individualizing erythropoietin dosages in hemodialysis patients

Jürgen Schmidhuber, José David Martín-Guerrero, Emilio Soria-Olivas, 2009, Expert Syst. Appl..

Active Guidance for a Finless Rocket Using Neuroevolution

Risto Miikkulainen, Faustino J. Gomez, R. Miikkulainen, 2003, GECCO.

Improving the Asymptotic Performance of Markov Chain Monte-Carlo by Inserting Vortices

Yi Sun, Jürgen Schmidhuber, Faustino J. Gomez, 2010, NIPS.

Efficient Non-linear Control Through Neuroevolution

Risto Miikkulainen, Jürgen Schmidhuber, Faustino J. Gomez, 2006, ECML.

Accelerated Neural Evolution through Cooperatively Coevolved Synapses

Risto Miikkulainen, Jürgen Schmidhuber, Faustino J. Gomez, 2008, J. Mach. Learn. Res..

Compressed Network Complexity Search

Jürgen Schmidhuber, Jan Koutník, Faustino J. Gomez, 2012, PPSN.

A Frequency-Domain Encoding for Neuroevolution pdf

Jürgen Schmidhuber, Jan Koutník, Faustino J. Gomez, 2012, ArXiv.

A System for Robotic Heart Surgery that Learns to Tie Knots Using Recurrent Neural Networks

Jürgen Schmidhuber, Alois Knoll, Faustino J. Gomez, 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Incremental Basis Construction from Temporal Difference Error

Yi Sun, Jürgen Schmidhuber, Faustino J. Gomez, 2011, ICML.

Complexity search for compressed neural networks

Jürgen Schmidhuber, Jan Koutník, Faustino J. Gomez, 2012, GECCO '12.

Understanding Locally Competitive Networks pdf

Jürgen Schmidhuber, Jonathan Masci, Faustino J. Gomez, 2014, ICLR.

Ontogenetic and Phylogenetic Reinforcement Learning

Julian Togelius, Tom Schaul, Jürgen Schmidhuber, 2009, Künstliche Intell..

A Clockwork RNN

Jürgen Schmidhuber, Jan Koutník, Klaus Greff, 2014, ICML.

Evolving neural networks in compressed weight space

Jürgen Schmidhuber, Jan Koutník, Faustino J. Gomez, 2010, GECCO '10.

Evolino for recurrent support vector machines pdf

Jürgen Schmidhuber, Faustino J. Gomez, Daan Wierstra, 2005, ESANN.

Evolving large-scale neural networks for vision-based TORCS

Jürgen Schmidhuber, Jan Koutník, Faustino J. Gomez, 2013, FDG.

Generalized Compressed Network Search

Jürgen Schmidhuber, Faustino J. Gomez, Rupesh Kumar Srivastava, 2012, PPSN.

Deep Networks with Internal Selective Attention through Feedback Connections

Jürgen Schmidhuber, Marijn F. Stollenga, Jonathan Masci, 2014, NIPS.

Scalable Neuroevolution for Reinforcement Learning

Faustino J. Gomez, F. Gomez, 2012, TPNC.

When Novelty Is Not Enough

Faustino J. Gomez, Giuseppe Cuccu, F. Gomez, 2011, EvoApplications.

Curiosity-driven optimization

Tom Schaul, Yi Sun, Jürgen Schmidhuber, 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).

Block Diagonal Natural Evolution Strategies

Faustino J. Gomez, Giuseppe Cuccu, 2012, PPSN.

Transfer of Neuroevolved Controllers in Unstable Domains

Risto Miikkulainen, Faustino J. Gomez, R. Miikkulainen, 2004, GECCO.

Evolino: Hybrid Neuroevolution/Optimal Linear Search for Sequence Learning

Jürgen Schmidhuber, Faustino J. Gomez, Daan Wierstra, 2005, IJCAI.

Learning what to ignore: Memetic climbing in topology and weight space

Julian Togelius, Jürgen Schmidhuber, Faustino J. Gomez, 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

Faustino J. Gomez, Vincent Graziano, Mark B. Ring, 2011, ArXiv.

Countering Poisonous Inputs with Memetic Neuroevolution

Julian Togelius, Tom Schaul, Jürgen Schmidhuber, 2008, PPSN.

Nascence Project: Nanoscale Engineering for Novel Computation Using Evolution

Julian Francis Miller, Gunnar Tufte, Faustino J. Gomez, 2012, Int. J. Unconv. Comput..

Measuring and Optimizing Behavioral Complexity for Evolutionary Reinforcement Learning

Julian Togelius, Jürgen Schmidhuber, Faustino J. Gomez, 2009, ICANN.

NAIS-Net: Stable Deep Networks from Non-Autonomous Differential Equations

Christian Osendorfer, Jonathan Masci, Faustino J. Gomez, 2018, NeurIPS.

Incremental Evolution of Complex General Behavior

Risto Miikkulainen, Faustino J. Gomez, R. Miikkulainen, 1997, Adapt. Behav..

Modular deep belief networks that do not forget

Jürgen Schmidhuber, Faustino J. Gomez, Leo Pape, 2011, The 2011 International Joint Conference on Neural Networks.

Compete to Compute

Jürgen Schmidhuber, Jonathan Masci, Faustino J. Gomez, 2013, NIPS.

Evolving deep unsupervised convolutional networks for vision-based reinforcement learning

Jürgen Schmidhuber, Jan Koutník, Faustino J. Gomez, 2014, GECCO.

Planning to Be Surprised: Optimal Bayesian Exploration in Dynamic Environments

Yi Sun, Jürgen Schmidhuber, Faustino J. Gomez, 2011, AGI.

Automatic design of novel potential 3CLpro and PLpro inhibitors pdf

Saeed Saremi, Jonathan Masci, Faustino J. Gomez, 2021, ArXiv.

Intrinsically Motivated Evolutionary Search for Vision-Based Reinforcement Learning

Faustino J. Gomez, Giuseppe Cuccu, Faustino Gomez, 2011 .

PhD Thesis: Robust Non-Linear Control through Neuroevolution

Faustino J. Gomez, Faustino Gomez, 2003 .

Recurrent Support Vector Machines

Faustino J. Gomez, J. Schmidhuber, Daan Wierstra, 2005 .

1 5 D ec 2 00 5 Evolino for Recurrent Support Vector Machines

Faustino J. Gomez, J. Schmidhuber, Daan Wierstra, 2022 .

Model-Based Active Exploration pdf

Wojciech Jaskowski, Faustino J. Gomez, Faustino Gomez, 2018, ICML.

Connectionist Temporal Classiﬁcation: Labelling Unsegmented Sequence Data with Recurrent Neural Networks

Faustino J. Gomez, Jürgen Schmidhuber, Alex Graves, 2022 .

Automatic design of novel potential 3CLpro and PLpro inhibitors

Saeed Saremi, Jonathan Masci, Faustino J. Gomez, 2021, ArXiv.

Robust non-linear control through neuroevolution

Risto Miikkulainen, Faustino J. Gomez, Faustino Gomez, 2003 .

2-D Pole Balancing with Recurrent Evolutionary Networks

Risto Miikkulainen, Faustino J. Gomez, Faustino Gomez, 1998 .