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Richard Socher

Richard Socher

D-Index & Metrics

Computer Science

D-Index
90
Citations
160587
World Ranking
588
National Ranking
314

Overview

Richard Socher is affiliated with you.com in the United States and specializes primarily in computer science, with a research focus on artificial intelligence. Their work spans multiple subfields, including molecular biology, computer vision and pattern recognition, radiology, nuclear medicine and imaging, as well as sociology and political science.

The main topics of Socher's research include:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Multimodal Machine Learning Applications
  • AI in Cancer Detection
  • Machine Learning in Bioinformatics
  • Neural Networks and Applications
  • Domain Adaptation and Few-Shot Learning

Socher has contributed extensively to scientific literature, with a total of 109 publications in computer science and related fields. Frequent publication venues include:

  • arXiv (Cornell University)
  • npj Digital Medicine
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Nature Biotechnology
  • Chemical Science

Some recent papers featuring Socher's work are:

  • Deep learning-enabled medical computer vision, 2021, npj Digital Medicine
  • Large language models generate functional protein sequences across diverse families, 2023, Nature Biotechnology
  • DivideMix: Learning with Noisy Labels as Semi-supervised Learning, 2020, arXiv (Cornell University)
  • Prototypical Contrastive Learning of Unsupervised Representations, 2020, arXiv (Cornell University)
  • Dye-sensitized solar cells under ambient light powering machine learning: towards autonomous smart sensors for the internet of things, 2020, Chemical Science

Frequent collaborators in Socher's research include:

  • Caiming Xiong
  • Andre Esteva
  • Nikhil Naik
  • Ali Madani
  • Steven C. H. Hoi

Best Publications

  • ImageNet: A large-scale hierarchical image database

    Jia Deng;Wei Dong;Richard Socher;Li-Jia Li

  • Glove: Global Vectors for Word Representation

    Jeffrey Pennington;Richard Socher;Christopher Manning

  • Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank

    Richard Socher;Alex Perelygin;Jean Wu;Jason Chuang

  • Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks

    Kai Sheng Tai;Richard Socher;Christopher D. Manning

  • Reasoning With Neural Tensor Networks for Knowledge Base Completion

    Richard Socher;Danqi Chen;Christopher D Manning;Andrew Ng

  • Knowing When to Look: Adaptive Attention via a Visual Sentinel for Image Captioning

    Jiasen Lu;Caiming Xiong;Devi Parikh;Richard Socher

  • Parsing Natural Scenes and Natural Language with Recursive Neural Networks

    Richard Socher;Cliff C. Lin;Chris Manning;Andrew Y. Ng

  • Semantic Compositionality through Recursive Matrix-Vector Spaces

    Richard Socher;Brody Huval;Christopher D. Manning;Andrew Y. Ng

  • Semi-Supervised Recursive Autoencoders for Predicting Sentiment Distributions

    Richard Socher;Jeffrey Pennington;Eric H. Huang;Andrew Y. Ng

  • A Deep Reinforced Model for Abstractive Summarization

    Romain Paulus;Caiming Xiong;Richard Socher

  • Improving Word Representations via Global Context and Multiple Word Prototypes

    Eric Huang;Richard Socher;Christopher Manning;Andrew Ng

  • Zero-Shot Learning Through Cross-Modal Transfer

    Richard Socher;Milind Ganjoo;Christopher D Manning;Andrew Ng

  • Ask me anything: dynamic memory networks for natural language processing

    Ankit Kumar;Ozan Irsoy;Peter Ondruska;Mohit Iyyer

  • Deep learning-enabled medical computer vision.

    Andre Esteva;Katherine Chou;Serena Yeung;Nikhil Naik

  • Parsing with Compositional Vector Grammars

    Richard Socher;John Bauer;Christopher D. Manning;Ng Andrew Y.

  • Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning

    Victor Zhong;Caiming Xiong;Richard Socher

  • Dynamic Pooling and Unfolding Recursive Autoencoders for Paraphrase Detection

    Richard Socher;Eric H. Huang;Jeffrey Pennin;Christopher D Manning

  • CTRL: A Conditional Transformer Language Model for Controllable Generation

    Nitish Shirish Keskar;Bryan McCann;Lav R. Varshney;Caiming Xiong

  • Zero-Shot Learning Through Cross-Modal Transfer

    Richard Socher;Milind Ganjoo;Hamsa Sridhar;Osbert Bastani

  • Grounded Compositional Semantics for Finding and Describing Images with Sentences

    Richard Socher;Andrej Karpathy;Quoc V. Le;Christopher D. Manning

  • Better Word Representations with Recursive Neural Networks for Morphology

    Thang Luong;Richard Socher;Christopher Manning

Frequent Co-Authors

Caiming Xiong
Caiming Xiong Salesforce (United States)
Christopher D. Manning
Christopher D. Manning Stanford University
Andrew Y. Ng
Andrew Y. Ng Stanford University
Steven C. H. Hoi
Steven C. H. Hoi Alibaba Group (China)
Dragomir R. Radev
Dragomir R. Radev Yale University
Lav R. Varshney
Lav R. Varshney University of Illinois at Urbana-Champaign
Larry S. Davis
Larry S. Davis University of Maryland, College Park
Philip S. Yu
Philip S. Yu University of Illinois at Chicago
Shafiq Joty
Shafiq Joty Salesforce (United States)
Zuxuan Wu
Zuxuan Wu Fudan University

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