Brandon M Stewart
Artificial Intelligence · 2013–2021
A researcher in the Science corpus: 10 papers; trusts 167 researchers and is trusted by 15 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 220 citations into it; #14,067 of 35,345 by trust here, #15,004 by citations
- Natural Language Processing — 124 citations into it; #4,535 of 5,688 by trust here, #4,983 by citations
- Information Systems — 76 citations into it
- Statistics and Probability — 71 citations into it
- Causal Inference & Discovery — 41 citations into it; #283 of 364 by trust here, #249 by citations
- Computer Vision and Pattern Recognition — 39 citations into it
- General Social Sciences — 37 citations into it; #54 of 274 by trust here, #34 by citations
- Representation & Self-Supervised Learning — 33 citations into it
Whom Brandon M Stewart trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- David M. Blei
- Justin Grimmer
- Michael I. Jordan
- Andrew Y. Ng
- Geoffrey E. Hinton
- Yehuda Koren
- Radford M. Neal
- Yoshua Bengio
- Diederik P. Kingma
- Chong Wang
Who trusts Brandon M Stewart overall
- Margaret E. Roberts
- Niels D. Goet
- Zachary C. Steinert-Threlkeld
- Christian Fong
- In Song Kim
- Carina Jacobi
- Matthew J. Denny
- Dustin Tingley
- Yang Bao
- Katherine A. Keith
Papers from Brandon M Stewart's perspective
Ordered by how strongly the researchers Brandon M Stewart 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)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Learning Multiple Layers of Features from Tiny Images
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
Their papers
- Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond (2021) — 330 citations
- A Model of Text for Experimentation in the Social Sciences (2016) — 658 citations
- A La Carte Embedding: Cheap but Effective Induction of Semantic Feature Vectors (2018) — 109 citations
- How algorithmic confounding in recommendation systems increases homogeneity and decreases utility (2017) — 397 citations
- How to make causal inferences using texts (2018) — 185 citations
- Adjusting for Confounding with Text Matching (2020) — 120 citations
- stm: An R Package for Structural Topic Models (2019) — 1,632 citations
- Computer-Assisted Text Analysis for Comparative Politics (2015) — 468 citations
- Structural Topic Models for Open‐Ended Survey Responses (2014) — 1,756 citations
- Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts (2013)