Payam Adineh

2019

A researcher in the Science corpus: 1 paper; trusts 0 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Papers from Payam Adineh's perspective

Ordered by how strongly the researchers Payam Adineh trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Convolutional Neural Networks for Sentence Classification
  2. Universal Language Model Fine-tuning for Text Classification
  3. Data Mining Practical Machine Learning Tools and Techniques
  4. A Stylometric Inquiry into Hyperpartisan and Fake News (Annual Meeting of the Association for Computational Linguistics)
  5. Language Models are Unsupervised Multitask Learners
  6. GloVe: Global Vectors for Word Representation
  7. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
  8. Distributed Representations of Words and Phrases and their Compositionality (Neural Information Processing Systems)
  9. ImageNet classification with deep convolutional neural networks
  10. Efficient Estimation of Word Representations in Vector Space

Their papers