Iñigo Casanueva
Artificial Intelligence · 2015–2020
A researcher in the Science corpus: 8 papers; trusts 65 researchers and is trusted by 30 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 170 citations into it; #7,067 of 35,345 by trust here, #4,316 by citations
- Natural Language Processing — 137 citations into it; #2,167 of 5,688 by trust here, #1,235 by citations
- Computer Vision and Pattern Recognition — 27 citations into it
- Reinforcement Learning — 20 citations into it
- Model Architectures — 14 citations into it
- Representation & Self-Supervised Learning — 9 citations into it
Whom Iñigo Casanueva trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Matthew Henderson
- Geoffrey E. Hinton
- Richard S. Sutton
- Yoshua Bengio
- Milica Gasic
- Ilya Sutskever
- Diederik P. Kingma
- Matthew E. Peters
- Alex Krizhevsky
- Oriol Vinyals
Who trusts Iñigo Casanueva overall
- Minlie Huang
- Ivan Vulic
- Christian Geishauser
- Paweł Budzianowski
- Pei-hao Su
- Kaixiang Mo
- Shikib Mehri
- Prakhar Gupta
- Carel van Niekerk
- Congyin Xia
Papers from Iñigo Casanueva's perspective
Ordered by how strongly the researchers Iñigo Casanueva trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- 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
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
Their papers
- MultiWOZ - A Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue Modelling (2018) — 1,527 citations
- A Repository of Conversational Datasets (2019) — 97 citations
- Efficient Intent Detection with Dual Sentence Encoders (2020) — 640 citations
- Towards end-to-end multi-domain dialogue modelling (2018) — 18 citations
- ConveRT: Efficient and Accurate Conversational Representations from Transformers (2019) — 214 citations
- Knowledge transfer between speakers for personalised dialogue management (2015) — 47 citations
- Feudal Reinforcement Learning for Dialogue Management in Large Domains (2018) — 50 citations
- Variational Cross-domain Natural Language Generation for Spoken Dialogue Systems (2018) — 14 citations