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Computer Science

D-Index
37
Citations
6175
World Ranking
10713
National Ranking
4476

Overview

Taylor Berg-Kirkpatrick is a researcher affiliated with the University of California, San Diego in the United States. Their work mainly spans the field of computer science, with a focus on artificial intelligence, computer vision and pattern recognition, and signal processing. Their research also extends into cognitive neuroscience and music.

The scientist's publication record includes 260 works primarily related to computer science. Key subfields within their research encompass:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Cognitive Neuroscience
  • Music

The major topics they address in their work include:

  • Music and Audio Processing
  • Topic Modeling
  • Natural Language Processing Techniques
  • Music Technology and Sound Studies
  • Speech and Audio Processing
  • Neuroscience and Music Perception
  • Multimodal Machine Learning Applications

Frequent venues for their publications highlight a strong presence in preprint and conference proceedings, including:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  • ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Recent papers authored or co-authored by the researcher include:

  • Towards a Unified View of Parameter-Efficient Transfer Learning, 2021, arXiv (Cornell University)
  • HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound Classification and Detection, 2022, ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • A Probabilistic Formulation of Unsupervised Text Style Transfer, 2020, arXiv (Cornell University)
  • Mix and Match: Learning-free Controllable Text Generation using Energy Language Models, 2022, Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  • Zero-Shot Audio Source Separation through Query-Based Learning from Weakly-Labeled Data, 2022, Proceedings of the AAAI Conference on Artificial Intelligence

Taylor Berg-Kirkpatrick has collaborated frequently with the following co-authors:

  • Julian McAuley
  • Shlomo Dubnov
  • Fatemehsadat Mireshghallah
  • Hao-Wen Dong
  • Kartik Goyal

Best Publications

  • Learning Bilingual Lexicons from Monolingual Corpora

    Aria Haghighi;Percy Liang;Taylor Berg-Kirkpatrick;Dan Klein

  • Speaker-Follower Models for Vision-and-Language Navigation

    Daniel Fried;Ronghang Hu;Volkan Cirik;Anna Rohrbach

  • Improved variational autoencoders for text modeling using dilated convolutions

    Zichao Yang;Zhiting Hu;Ruslan Salakhutdinov;Taylor Berg-Kirkpatrick

  • Large-Scale Contrastive Language-Audio Pretraining with Feature Fusion and Keyword-to-Caption Augmentation

    Unknown

  • Learning Whom to Trust with MACE

    Dirk Hovy;Taylor Berg-Kirkpatrick;Ashish Vaswani;Eduard Hovy

  • Towards a Unified View of Parameter-Efficient Transfer Learning

    Junxian He;Chunting Zhou;Xuezhe Ma;Taylor Berg-Kirkpatrick

  • Painless Unsupervised Learning with Features

    Taylor Berg-Kirkpatrick;Alexandre Bouchard-Côté;John DeNero;Dan Klein

  • Unsupervised Text Style Transfer using Language Models as Discriminators

    Zichao Yang;Zhiting Hu;Chris Dyer;Eric P. Xing

  • Jointly Learning to Extract and Compress

    Taylor Berg-Kirkpatrick;Dan Gillick;Dan Klein

  • Lagging Inference Networks and Posterior Collapse in Variational Autoencoders

    Junxian He;Daniel Spokoyny;Graham Neubig;Taylor Berg-Kirkpatrick

  • HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound Classification and Detection

    Unknown

  • An Empirical Investigation of Statistical Significance in NLP

    Taylor Berg-Kirkpatrick;David Burkett;Dan Klein

  • Learning-Based Single-Document Summarization with Compression and Anaphoricity Constraints

    Greg Durrett;Taylor Berg-Kirkpatrick;Dan Klein

  • Beyond BLEU: Training Neural Machine Translation with Semantic Similarity.

    John Wieting;Taylor Berg-Kirkpatrick;Kevin Gimpel;Graham Neubig

  • A Probabilistic Formulation of Unsupervised Text Style Transfer

    Junxian He;Xinyi Wang;Graham Neubig;Taylor Berg-Kirkpatrick

  • Learning to Describe Differences Between Pairs of Similar Images

    Harsh Jhamtani;Taylor Berg-Kirkpatrick

  • Tools for Automated Analysis of Cybercriminal Markets

    Rebecca S. Portnoff;Sadia Afroz;Greg Durrett;Jonathan K. Kummerfeld

  • SPINE: SParse Interpretable Neural Embeddings

    Anant Subramanian;Danish Pruthi;Harsh Jhamtani;Taylor Berg-Kirkpatrick

  • Using accelerometers to remotely and automatically characterize behavior in small animals.

    Talisin T. Hammond;Dwight Springthorpe;Rachel E. Walsh;Taylor Berg-Kirkpatrick

  • Phylogenetic Grammar Induction

    Taylor Berg-Kirkpatrick;Dan Klein

  • Using Syntax to Ground Referring Expressions in Natural Images.

    Volkan Cirik;Taylor Berg-Kirkpatrick;Louis-Philippe Morency

  • A Surprisingly Effective Fix for Deep Latent Variable Modeling of Text

    Bohan Li;Junxian He;Graham Neubig;Taylor Berg-Kirkpatrick

Frequent Co-Authors

Graham Neubig
Graham Neubig Carnegie Mellon University
Daniel Klein
Daniel Klein University of California, Berkeley
Eduard Hovy
Eduard Hovy Carnegie Mellon University
Julian McAuley
Julian McAuley University of California, San Diego
Louis-Philippe Morency
Louis-Philippe Morency Carnegie Mellon University
Chris Dyer
Chris Dyer Google (United States)
Zhiting Hu
Zhiting Hu University of California, San Diego
Kevin Gimpel
Kevin Gimpel Toyota Technological Institute at Chicago
Eric P. Xing
Eric P. Xing Mohamed bin Zayed University of Artificial Intelligence

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