Shubham Gupta

发表

Attentive Recurrent Comparators pdf

Ambedkar Dukkipati, Shubham Gupta, Pranav Shyam, 2017, ICML.

International Conference on Innovative Computing and Communication (ICICC 2020) A Performance Comparisons of Machine Learning Classification Techniques for Job Titles Using Job Descriptions

Narina Thakur, Shubham Gupta, Shreyans Mittal, 2020 .

Equipping SBMs with RBMs: An Explainable Approach for Analysis of Networks with Covariates

Rui M. Castro, Ambedkar Dukkipati, Shubham Gupta, 2022 .

Differentiable Rule Induction with Learned Relational Features

Yusik Kim, R. Kusters, Shubham Gupta, 2022, ArXiv.

A Survey on Temporal Graph Representation Learning and Generative Modeling

Srikanta J. Bedathur, Shubham Gupta, 2022, ArXiv.

TIGGER: Scalable Generative Modelling for Temporal Interaction Graphs

Srikanta J. Bedathur, Shubham Gupta, Sayan Ranu, 2022, AAAI.

Consistency of Constrained Spectral Clustering under Graph Induced Fair Planted Partitions

Ambedkar Dukkipati, Shubham Gupta, 2021, NeurIPS.

Probabilistic View of Multi-agent Reinforcement Learning: A Unified Approach

Ambedkar Dukkipati, Shubham Gupta, Ambedkar Dukkipati, 2019 .

Networked Multi-Agent Reinforcement Learning with Emergent Communication pdf

Rishi Hazra, Ambedkar Dukkipati, Shubham Gupta, 2020, AAMAS.

Winning an Election: On Emergent Strategic Communication in Multi-Agent Networks

Ambedkar Dukkipati, Shubham Gupta, 2019, AAMAS.

Active2 Learning: Actively reducing redundancies in Active Learning methods for Sequence Tagging and Machine Translation pdf

Ambedkar Dukkipati, Rishi Hazra, Parag Dutta, 2021, NAACL 2021.

Neural Latent Space Model for Dynamic Networks and Temporal Knowledge Graphs

Ambedkar Dukkipati, Tony Gracious, Arun Kanthali, 2021, AAAI.

A Generative Model for Dynamic Networks with Applications

Gaurav Sharma, Ambedkar Dukkipati, Shubham Gupta, 2018, AAAI.

Evolving Latent Space Model for Dynamic Networks pdf

Gaurav Sharma, Ambedkar Dukkipati, Shubham Gupta, 2018, ArXiv.

Pure Exploration with Structured Preference Feedback pdf

Aadirupa Saha, Sumeet Katariya, Shubham Gupta, 2021, ArXiv.

Active^2 Learning: Actively reducing redundancies in Active Learning methods for Sequence Tagging and Machine Translation

Rishi Hazra, Ambedkar Dukkipati, Shubham Gupta, 2019, NAACL.

Restricted Boltzmann Stochastic Block Model: A Generative Model for Networks with Attributes pdf

Ambedkar Dukkipati, Shubham Gupta, Rui M. Castro, 2019, ArXiv.

GRAFENNE: Learning on Graphs with Heterogeneous and Dynamic Feature Sets

Srikanta J. Bedathur, Shubham Gupta, Sayan Ranu, 2023, ICML.

On Voting Strategies and Emergent Communication

Ambedkar Dukkipati, Shubham Gupta, 2019, ArXiv.

GSHOT: Few-shot Generative Modeling of Labeled Graphs

Srikanta J. Bedathur, Shubham Gupta, Sayan Ranu, 2023, arXiv.org.

On consistency of constrained spectral clustering under representation-aware stochastic block model

Ambedkar Dukkipati, Shubham Gupta, 2022, ArXiv.

Protecting Individual Interests across Clusters: Spectral Clustering with Guarantees pdf

Ambedkar Dukkipati, Shubham Gupta, Ambedkar Dukkipati, 2021, ArXiv.

Active^2 Learning: Actively reducing redundancies in Active Learning methods for Sequence Tagging and Machine Translation

Mohammed Abdul Qaathir, Ambedkar Dukkipati, Shubham Gupta, 2021, NAACL.

CoviHawkes: Temporal Point Process and Deep Learning based Covid-19 forecasting for India pdf

Ambedkar Dukkipati, Tony Gracious, Shubham Gupta, 2021, ArXiv.