Thomas F. Icard III
Artificial Intelligence · 2014–2023
A researcher in the Science corpus: 7 papers; trusts 30 researchers and is trusted by 9 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 88 citations into it
- Natural Language Processing — 59 citations into it
- Evaluation & Benchmarks — 21 citations into it
- Causal Inference & Discovery — 16 citations into it
- Model Architectures — 14 citations into it
- Statistics and Probability — 14 citations into it
- Probabilistic & Bayesian Methods — 10 citations into it
Whom Thomas F. Icard III trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yorick Wilks
- Judea Pearl
- Bill MacCartney
- Christopher D. Manning
- Ido Dagan
- Donald B. Rubin
- J. Benthem
- Tom L. Burr
- Gabor Angeli
- Jin Tian
Who trusts Thomas F. Icard III overall
- Gabor Angeli
- Lasha Abzianidze
- Lauri Karttunen
- Christopher D. Manning
- Atticus Geiger
- Kaj Bostrom
- Samuel R. Bowman
- Christopher Potts
- Melvin Johnson
- Neha Nayak Kennard
Papers from Thomas F. Icard III's perspective
Ordered by how strongly the researchers Thomas F. Icard III trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Long Short-Term Memory
- 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
- GloVe: Global Vectors for Word Representation
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
Their papers
- On the Opportunities and Risks of Foundation Models (2021) — 6,923 citations
- Holistic Evaluation of Language Models (2023) — 1,863 citations
- On Pearl’s Hierarchy and the Foundations of Causal Inference (2022) — 346 citations
- Causal Abstractions of Neural Networks (2021) — 428 citations
- A Monotonicity Calculus and Its Completeness (2017) — 12 citations
- Neural-Symbolic Learning and Reasoning: Contributions and Challenges (2015) — 201 citations
- Recent Progress on Monotonicity (2014)