P. K. Srijith

Orcid: 0000-0002-2820-0835

According to our database1, P. K. Srijith authored at least 46 papers between 2012 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

On csauthors.net:

Bibliography

2024
Transformer based Multitask Learning for Image Captioning and Object Detection.
CoRR, 2024

2023
Continual Learning with Dependency Preserving Hypernetworks.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Continuous Depth Recurrent Neural Differential Equations.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Time-to-Event Modeling with Hypernetwork based Hawkes Process.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Event Uncertainty using Ensemble Neural Hawkes Process.
Proceedings of the 6th Joint International Conference on Data Science & Management of Data (10th ACM IKDD CODS and 28th COMAD), 2023

2022
Towards Generalized and Explainable Long-Range Context Representation for Dialogue Systems.
CoRR, 2022

HyperHawkes: Hypernetwork based Neural Temporal Point Process.
CoRR, 2022

Galaxy morphology classification using neural ordinary differential equations.
Astron. Comput., 2022

Cosmic Ray rejection with attention augmented deep learning.
Astron. Comput., 2022

Hawkes Process Classification through Discriminative Modeling of Text.
Proceedings of the International Joint Conference on Neural Networks, 2022

Predicting Reputation Score of Users in Stack-overflow with Alternate Data.
Proceedings of the 14th International Joint Conference on Knowledge Discovery, 2022

Cosmic Ray Detection in Astronomical Images via Dictionary Learning and Sparse Representation.
Proceedings of the 30th European Signal Processing Conference, 2022

Latent Time Neural Ordinary Differential Equations.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Bayesian Neural Hawkes Process for Event Uncertainty Prediction.
CoRR, 2021

Bi-Directional Recurrent Neural Ordinary Differential Equations for Social Media Text Classification.
CoRR, 2021

Monte Carlo DropBlock for Modelling Uncertainty in Object Detection.
CoRR, 2021

Improving Robustness and Uncertainty Modelling in Neural Ordinary Differential Equations.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

Subset-of-data variational inference for deep Gaussian-processes regression.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

CAM-GAN: Continual Adaptation Modules for Generative Adversarial Networks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Delay Differential Neural Networks.
Proceedings of the ICMLT 2021: 6th International Conference on Machine Learning Technologies, Jeju Island, Republic of Korea, April 23, 2021

Adiabatic Quantum Feature Selection for Sparse Linear Regression.
Proceedings of the Computational Science - ICCS 2021, 2021

Bayesian Generative Adversarial Nets with Dropout Inference.
Proceedings of the CODS-COMAD 2021: 8th ACM IKDD CODS and 26th COMAD, 2021

Learning Multi-Sense Word Distributions using Approximate Kullback-Leibler Divergence.
Proceedings of the CODS-COMAD 2021: 8th ACM IKDD CODS and 26th COMAD, 2021

Multi-view hypergraph convolution network for semantic annotation in LBSNs.
Proceedings of the ASONAM '21: International Conference on Advances in Social Networks Analysis and Mining, Virtual Event, The Netherlands, November 8, 2021

2020
Evaluation of Deep Gaussian Processes for Text Classification.
Proceedings of The 12th Language Resources and Evaluation Conference, 2020

STM-GAN: Sequentially Trained Multiple Generators for Mitigating Mode Collapse.
Proceedings of the Neural Information Processing - 27th International Conference, 2020

Improving Adaptive Bayesian Optimization with Spectral Mixture Kernel.
Proceedings of the Neural Information Processing - 27th International Conference, 2020

HAP-SAP: Semantic Annotation in LBSNs using Latent Spatio-Temporal Hawkes Process.
Proceedings of the SIGSPATIAL '20: 28th International Conference on Advances in Geographic Information Systems, 2020

Decision Making under Uncertainty with Convolutional Deep Gaussian Processes.
Proceedings of the CoDS-COMAD 2020: 7th ACM IKDD CoDS and 25th COMAD, 2020

2019
Leveraging Social Media Towards Understanding Anti-Vaccination Campaigns.
Proceedings of the 11th International Conference on Communication Systems & Networks, 2019

2018
Deep Gaussian Processes with Convolutional Kernels.
CoRR, 2018

A Bayesian Point Process Model for User Return Time Prediction in Recommendation Systems.
Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization, 2018

Accelerating Hawkes process for event history data: Application to social networks and recommendation systems.
Proceedings of the 10th International Conference on Communication Systems & Networks, 2018

Classification of Short-Texts Generated During Disasters: A Deep Neural Network Based Approach.
Proceedings of the IEEE/ACM 2018 International Conference on Advances in Social Networks Analysis and Mining, 2018

2017
Sub-story detection in Twitter with hierarchical Dirichlet processes.
Inf. Process. Manag., 2017

Longitudinal Modeling of Social Media with Hawkes Process Based on Users and Networks.
Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017, Sydney, Australia, July 31, 2017

2016
Gaussian Process Pseudo-Likelihood Models for Sequence Labeling.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

Studying the Temporal Dynamics of Word Co-occurrences: An Application to Event Detection.
Proceedings of the Tenth International Conference on Language Resources and Evaluation LREC 2016, 2016

Hawkes Processes for Continuous Time Sequence Classification: an Application to Rumour Stance Classification in Twitter.
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, 2016

2015
Modeling Tweet Arrival Times using Log-Gaussian Cox Processes.
Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, 2015

2014
Gaussian Process Pseudo-Likelihood Models for Sequence Labeling.
CoRR, 2014

Gaussian Process Multi-task Learning Using Joint Feature Selection.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

2013
Semi-supervised Gaussian Process Ordinal Regression.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

2012
Validation Based Sparse Gaussian Processes for Ordinal Regression.
Proceedings of the Neural Information Processing - 19th International Conference, 2012

Multi-Task Learning Using Shared and Task Specific Information.
Proceedings of the Neural Information Processing - 19th International Conference, 2012

A Probabilistic Least Squares Approach to Ordinal Regression.
Proceedings of the AI 2012: Advances in Artificial Intelligence, 2012


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