Bogdan Gabrys
Artificial Intelligence · 2000–2020
A researcher in the Science corpus: 14 papers; trusts 525 researchers and is trusted by 27 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 216 citations into it; #8,965 of 35,345 by trust here, #10,942 by citations
- Computer Vision and Pattern Recognition — 121 citations into it; #8,553 of 21,575 by trust here, #12,992 by citations
- Optimization & Training — 56 citations into it
- Neural Architecture Search & AutoML — 52 citations into it
- Model Architectures — 40 citations into it
- Evaluation & Benchmarks — 39 citations into it
- Management Science and Operations Research — 36 citations into it; #7,826 of 11,946 by trust here, #8,062 by citations
- Control and Systems Engineering — 33 citations into it; #3,003 of 8,257 by trust here, #2,612 by citations
Whom Bogdan Gabrys trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Geoffrey E. Hinton
- Yoshua Bengio
- Frank Hutter
- Kaiming He
- Diederik P. Kingma
- Ilya Sutskever
- Yann LeCun
- Quoc V. Le
- Ronald J. Williams
Who trusts Bogdan Gabrys overall
- Pilar Rey del Castillo
- Mirko Kück
- Yuchen Jiang
- Marc-André Zöller
- Petr Kadlec
- Jesús Cardeñosa Lera
- Ishan Misra
- Michal Wozniak
- Guillaume Chanel
- Iftikhar Ahmad
Papers from Bogdan Gabrys's perspective
Ordered by how strongly the researchers Bogdan Gabrys 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)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- 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
- Metalearning: a survey of trends and technologies (2013) — 377 citations
- Classifier selection for majority voting (2005) — 661 citations
- Meta-learning for time series forecasting and forecast combination (2010) — 261 citations
- NATS-Bench: Benchmarking NAS Algorithms for Architecture Topology and Size (2020) — 213 citations
- AVATAR - Machine Learning Pipeline Evaluation Using Surrogate Model (2020) — 12 citations
- AutoHAS: Differentiable Hyper-parameter and Architecture Search (2020) — 24 citations
- Foundations and Modeling of Dynamic Networks Using Dynamic Graph Neural Networks: A Survey (2020) — 336 citations
- AutoHAS: Efficient Hyperparameter and Architecture Search. (2020) — 40 citations
- Modelling Multi-Component Predictive Systems as Petri Nets (2017) — 10 citations
- Towards Automatic Composition of Multicomponent Predictive Systems (2016) — 23 citations
- Review of adaptation mechanisms for data-driven soft sensors (2011) — 501 citations
- Data-driven Soft Sensors in the process industry (2009) — 1,730 citations
- General fuzzy min-max neural network for clustering and classification (2000) — 427 citations
- An Overview of Classifier Fusion Methods (2000) — 428 citations