Brandon Duderstadt
Artificial Intelligence · 2018–2026
A researcher in the Science corpus: 20 papers; trusts 170 researchers and is trusted by 18 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 202 citations into it; #10,712 of 35,345 by trust here, #1,904 by citations
- Computer Vision and Pattern Recognition — 87 citations into it
- Representation & Self-Supervised Learning — 83 citations into it; #2,307 of 3,145 by trust here, #717 by citations
- Large Language Models — 71 citations into it; #589 of 799 by trust here, #533 by citations
- Natural Language Processing — 71 citations into it
- Evaluation & Benchmarks — 46 citations into it; #2,283 of 3,147 by trust here, #2,545 by citations
- Information Retrieval & Search — 34 citations into it
- Statistics and Probability — 26 citations into it; #7,597 of 12,932 by trust here, #3,411 by citations
Whom Brandon Duderstadt trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yoshua Bengio
- Geoffrey E. Hinton
- Nils Reimers
- Diederik P. Kingma
- Alex Krizhevsky
- Ilya Sutskever
- Yann LeCun
- Kaiming He
- Alec Radford
- Alex Graves
Who trusts Brandon Duderstadt overall
- Hayden S. Helm
- Carey E. Priebe
- Aranyak Acharyya
- Hong-Liu Cao
- Youngser Park
- M. Trosset
- Bowen Zhang
- Hayato Tsukagoshi
- Luke Merrick
- John X. Morris
Papers from Brandon Duderstadt's perspective
Ordered by how strongly the researchers Brandon Duderstadt 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)
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- 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
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- A partition-based similarity for classification distributions (2020) — 6 citations
- Comparing Foundation Models using Data Kernels (2023) — 16 citations
- A Model of the Language Process (2026) — 1 citation
- Control Charts for Multi-agent Systems (2026) — 1 citation
- Toward A Digital Twin of U.S. Congress (2026) — 0 citations
- Wikivecs: A Fully Reproducible Vectorization of Multilingual Wikipedia (2025) — 1 citation
- NOMAD Projection (2025) — 0 citations
- Toward a digital twin of U.S. Congress (2025) — 1 citation
- CNS-Obsidian: A Neurosurgical Vision-Language Model Built From Scientific Publications. (2025) — 4 citations
- Training Sparse Mixture Of Experts Text Embedding Models (2025) — 44 citations
- Nomic Embed: Training a Reproducible Long Context Text Embedder (2024) — 418 citations
- Tracking the perspectives of interacting language models (2024) — 17 citations
- Statistical inference on black-box generative models in the data kernel perspective space (2024) — 12 citations
- Nomic Embed Vision: Expanding the Latent Space (2024) — 26 citations
- CoRNStack: High-Quality Contrastive Data for Better Code Ranking (2024) — 12 citations
- CoRNStack: High-Quality Contrastive Data for Better Code Retrieval and Reranking (2024) — 44 citations
- Towards Explainable and Accessible AI (2023) — 0 citations
- GPT4All: An Ecosystem of Open Source Compressed Language Models (2023) — 29 citations
- NeuroStorm: Accelerating Brain Science Discovery in the Cloud (2018) — 0 citations
- : Advancing Natural Language Processing for — 0 citations