Brian Strope
Artificial Intelligence · 2010–2019
A researcher in the Science corpus: 13 papers; trusts 121 researchers and is trusted by 25 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 195 citations into it; #7,596 of 35,345 by trust here, #2,070 by citations
- Natural Language Processing — 190 citations into it; #1,556 of 5,688 by trust here, #505 by citations
- Computer Vision and Pattern Recognition — 56 citations into it
- Model Architectures — 38 citations into it
- Evaluation & Benchmarks — 37 citations into it
- Representation & Self-Supervised Learning — 32 citations into it; #2,263 of 3,145 by trust here, #602 by citations
- Signal Processing — 13 citations into it
- Large Language Models — 12 citations into it
Whom Brian Strope trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Graves
- Yoshua Bengio
- Geoffrey E. Hinton
- Tomas Mikolov
- Yann LeCun
- Ilya Sutskever
- Sepp Hochreiter
- J. Urgen Schmidhuber
- Hynek Hermansky
- Oriol Vinyals
Who trusts Brian Strope overall
- Yinfei Yang
- Daniel Matthew Cer
- Andy Zeng
- Matthew Henderson
- Weidi Xu
- Jianmo Ni
- Jiwei Li
- Holger Schwenk
- Amin Ahmad
- Adji Bousso Dieng
Papers from Brian Strope's perspective
Ordered by how strongly the researchers Brian Strope trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- 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)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Universal Sentence Encoder (2018) — 2,093 citations
- Generating High-Quality and Informative Conversation Responses with Sequence-to-Sequence Models (2017) — 218 citations
- Learning Semantic Textual Similarity from Conversations (2018) — 167 citations
- Multilingual Universal Sentence Encoder for Semantic Retrieval (2019) — 534 citations
- Universal Sentence Encoder for English (2018) — 1,019 citations
- Efficient Natural Language Response Suggestion for Smart Reply (2017) — 514 citations
- Effective Parallel Corpus Mining using Bilingual Sentence Embeddings (2018) — 115 citations
- Improving Multilingual Sentence Embedding using Bi-directional Dual Encoder with Additive Margin Softmax (2019) — 124 citations
- Contextual LSTM (CLSTM) models for Large scale NLP tasks (2016) — 229 citations
- “Your Word is my Command”: Google Search by Voice: A Case Study (2010) — 253 citations
- Conversational Contextual Cues: The Case of Personalization and History for Response Ranking (2016) — 93 citations
- Unsupervised Testing Strategies for ASR (2011) — 15 citations
- Generating Long and Diverse Responses with Neural Conversation Models (2017) — 65 citations