Encode: life, the universe, and everything.

By S. Krams, J. Bromberg. 2013

138 citations recorded by the source corpus.

Subfields: Neurology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Neurology

1. Dawn Song
2. Eric P. Xing
3. Vitaly Feldman
4. Trevor Darrell
5. Anna Rohrbach
6. Kunal Talwar
7. Xiaodan Liang

Citations in the corpus

• An encyclopedia of mouse DNA elements (Mouse ENCODE) (2012, unknown): “Working copies of data standard documents are available as an appendix to the recently published User’s Guide to ENCODE Data [14] and at the home page of the ENCODE project [26].”
• Lossless Compression of Efficient Private Local Randomizers (2021, methodology): “Existence of such reference distribution is exactly the definition of the deletion version of local differential privacy [EFMRSTT20] and thus our results are easiest to describe in this model.”
• Hybrid Retrieval-Generation Reinforced Agent for Medical Image Report Generation (2018, background): “Beyond the traditional visual captioning task [41, 28, 43, 40, 18] that produces one single sentence, generating long and topic-coherent stories or reports to describe visual contents (images or videos) has recently attracted increasing research interests [19, 35, 22], posed as a more challenging an”
• Machine Learning for Integrating Data in Biology and Medicine: Principles, Practice, and Opportunities (2018, unknown): “To this aim, numerous research efforts, such as the Encyclopedia of DNA Elements (ENCODE) [1] (Section 5) and the Genotype-Tissue Expression (GTEx) [187] projects, have expanded the breadth of available data that lend themselves to protein function prediction (Figure 5).”
• Fooling Vision and Language Models Despite Localization and Attention Mechanism (2017, background): “Others have adopted this idea [15, 42, 46, 76] or extended it to perform attention over semantic concepts, or attributes [77, 79].”