Mario Giulianelli
Artificial Intelligence · 2018–2023
A researcher in the Science corpus: 4 papers; trusts 36 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 28 citations into it; #22,905 of 35,345 by trust here, #13,544 by citations
- Natural Language Processing — 28 citations into it; #4,113 of 5,688 by trust here, #2,888 by citations
- Representation & Self-Supervised Learning — 9 citations into it
- Cultural Studies — 8 citations into it
Whom Mario Giulianelli trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Hinrich Schütze
- Sepp Hochreiter
- Peter J. Rousseeuw
- Geoffrey E. Hinton
- Yoshua Bengio
- Diederik P. Kingma
- Ilya Sutskever
- Jacob Devlin
- J. Urgen Schmidhuber
- Alex Krizhevsky
Who trusts Mario Giulianelli overall
- Yonatan Belinkov
- John Hewitt
- Clara Meister
- Abhilasha Ravichander
- Nora Kassner
- Jaap Jumelet
- Christoph Alt
- Nils Rethmeier
- Bhuwan Dhingra
- Yair Lakretz
Papers from Mario Giulianelli's perspective
Ordered by how strongly the researchers Mario Giulianelli trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- Under the Hood: Using Diagnostic Classifiers to Investigate and Improve how Language Models Track Agreement Information (2018) — 202 citations
- Analysing Lexical Semantic Change with Contextualised Word Representations (2020) — 215 citations
- Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models (2023) — 266 citations
- Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models (2022) — 2,561 citations