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Partha Pratim Talukdar

Partha Pratim Talukdar

D-Index & Metrics

Computer Science

D-Index
49
Citations
10494
World Ranking
5852
National Ranking
54

Overview

Partha Pratim Talukdar is a researcher affiliated with Google (India) in India, specializing in Computer Science with a focus on Artificial Intelligence. Their body of work includes significant contributions to subfields such as Computer Vision and Pattern Recognition, Surgery, Materials Chemistry, and Plant Science.

The researcher's work spans several main topics including:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Text Readability and Simplification
  • Multimodal Machine Learning Applications
  • Advanced Graph Neural Networks
  • Speech Recognition and Synthesis
  • Machine Learning in Materials Science

Talukdar has published extensively, with key papers including:

  • MuRIL: Multilingual Representations for Indian Languages, 2021, arXiv (Cornell University)
  • ProteinGCN: Protein model quality assessment using Graph Convolutional Networks, 2020, bioRxiv (Cold Spring Harbor Laboratory)
  • Proceedings of the 16th International Conference on Educational Data Mining, 2023, Zenodo (CERN European Organization for Nuclear Research)
  • ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations, 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • P-SIF: Document Embeddings Using Partition Averaging, 2020, Proceedings of the AAAI Conference on Artificial Intelligence

Their frequent collaborators include Shikhar Vashishth, Bidisha Samanta, Shachi Dave, Soumya Sanyal, and Mingyu Feng.

Talukdar's publications are commonly found in venues such as:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Best Publications

  • Never-ending learning

    T. Mitchell;W. Cohen;E. Hruschka;P. Talukdar

  • Never-ending learning

    T. Mitchell;W. Cohen;E. Hruschka;P. Talukdar

  • Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings

    Apoorv Saxena;Aditay Tripathi;Partha P. Talukdar

  • HyTE: Hyperplane-based Temporally aware Knowledge Graph Embedding.

    Shib Sankar Dasgupta;Swayambhu Nath Ray;Partha P. Talukdar

  • Composition-based Multi-Relational Graph Convolutional Networks

    Shikhar Vashishth;Soumya Sanyal;Vikram Nitin;Partha Talukdar

  • Simultaneously uncovering the patterns of brain regions involved in different story reading subprocesses

    Leila Wehbe;Brian Murphy;Partha Talukdar;Alona Fyshe

  • InteractE: Improving Convolution-Based Knowledge Graph Embeddings by Increasing Feature Interactions

    Shikhar Vashishth;Soumya Sanyal;Vikram Nitin;Nilesh Agrawal

  • New Regularized Algorithms for Transductive Learning

    Partha Pratim Talukdar;Koby Crammer

  • RESIDE: Improving Distantly-Supervised Neural Relation Extraction using Side Information

    Shikhar Vashishth;Rishabh Joshi;Sai Suman Prayaga;Chiranjib Bhattacharyya

  • ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations

    Ekagra Ranjan;Soumya Sanyal;Partha Pratim Talukdar

  • Incorporating Vector Space Similarity in Random Walk Inference over Knowledge Bases

    Matt Gardner;Partha Talukdar;Jayant Krishnamurthy;Tom Mitchell

  • HyperGCN: A New Method of Training Graph Convolutional Networks on Hypergraphs

    Naganand Yadati;Madhav Nimishakavi;Prateek Yadav;Vikram Nitin

  • Learning Effective and Interpretable Semantic Models using Non-Negative Sparse Embedding

    Brian Murphy;Partha Talukdar;Tom Mitchell

  • Weakly-Supervised Acquisition of Labeled Class Instances using Graph Random Walks

    Partha Pratim Talukdar;Joseph Reisinger;Marius Pasca;Deepak Ravichandran

  • KVQA: Knowledge-Aware Visual Question Answering

    Sanket Shah;Anand Mishra;Naganand Yadati;Partha Pratim Talukdar

  • MuRIL: Multilingual Representations for Indian Languages.

    Simran Khanuja;Diksha Bansal;Sarvesh Mehtani;Savya Khosla

  • Automatic Code Assignment to Medical Text

    Koby Crammer;Mark Dredze;Kuzman Ganchev;Partha Pratim Talukdar

  • Graph-Based Semi-Supervised Learning

    Amarnag Subramanya;Partha Pratim Talukdar

  • FlexiFaCT: Scalable Flexible Factorization of Coupled Tensors on Hadoop

    Alex Beutel;Partha Pratim Talukdar;Abhimanu Kumar;Christos Faloutsos

  • The ORCHESTRA Collaborative Data Sharing System

    Zachary G. Ives;Todd J. Green;Grigoris Karvounarakis;Nicholas E. Taylor

  • A Re-evaluation of Knowledge Graph Completion Methods

    Zhiqing Sun;Shikhar Vashishth;Soumya Sanyal;Partha P. Talukdar

Frequent Co-Authors

Tom M. Mitchell
Tom M. Mitchell Carnegie Mellon University
Evangelos E. Papalexakis
Evangelos E. Papalexakis University of California, Riverside
Christos Faloutsos
Christos Faloutsos Carnegie Mellon University
Koby Crammer
Koby Crammer Technion – Israel Institute of Technology
Nicholas D. Sidiropoulos
Nicholas D. Sidiropoulos University of Virginia
Fernando Pereira
Fernando Pereira Google (United States)
William W. Cohen
William W. Cohen Carnegie Mellon University
Matt Gardner
Matt Gardner Allen Institute for Artificial Intelligence
Zachary G. Ives
Zachary G. Ives University of Pennsylvania
Mark Dredze
Mark Dredze Johns Hopkins University

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