Mantas Lukosevicius
Artificial Intelligence · 2007–2012
A researcher in the Science corpus: 4 papers; trusts 49 researchers and is trusted by 42 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 43 citations into it; #4,101 of 35,345 by trust here, #5,788 by citations
- Electrical and Electronic Engineering — 29 citations into it; #473 of 16,539 by trust here, #3,248 by citations
- Model Architectures — 27 citations into it; #662 of 2,278 by trust here, #621 by citations
- Cognitive Neuroscience — 21 citations into it; #7,769 of 10,852 by trust here, #8,086 by citations
- Optimization & Training — 13 citations into it; #1,091 of 2,601 by trust here, #855 by citations
- Signal Processing — 7 citations into it
- Scaling & Learning Theory — 5 citations into it
Whom Mantas Lukosevicius trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Herbert Jaeger
- Paul J. Werbos
- Ronald J. Williams
- Alex Graves
- Yoshua Bengio
- J. Urgen Schmidhuber
- Geoffrey E. Hinton
- Sepp Hochreiter
- David E. Rumelhart
- David Zipser
Who trusts Mantas Lukosevicius overall
- Herbert Jaeger
- Mingzhe Chen
- Christian A. Rössert
- Gouhei Tanaka
- Razvan Pascanu
- Johanni Brea
- Kelly W. Zhang
- Paul Dean
- Walid Saad
- Ursula Challita
Papers from Mantas Lukosevicius's perspective
Ordered by how strongly the researchers Mantas Lukosevicius trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- 2007 Special Issue: Optimization and applications of echo state networks with leaky- integrator neurons (2007) — 954 citations
- Reservoir computing approaches to recurrent neural network training (2009) — 2,939 citations
- A Practical Guide to Applying Echo State Networks (2012) — 862 citations
- Reservoir Computing Trends (2012) — 383 citations