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2020 – today
- 2025
[j5]Manisha Dubey
, Ragja Palakkadavath, P. K. Srijith:
Bayesian neural hawkes process for event uncertainty prediction. Int. J. Data Sci. Anal. 20(2): 573-587 (2025)- [c47]Arkaprava Majumdar, M. Anand Krishna, P. K. Srijith:
Neural Wave Equation for Irregularly Sampled Sequence Data. ICLR 2025 - [c46]Dupati Srikar Chandra, P. K. Srijith, Dana Rezazadegan, Chris McCarthy:
Linked Adapters: Linking Past and Future to Present for Effective Continual Learning. PAKDD (1) 2025: 278-290 - [c45]Sayanta Adhikari, Dupati Srikar Chandra, P. K. Srijith, Pankaj Wasnik, Naoyuki Onoe:
AdaPrefix++: Integrating Adapters, Prefixes and Hypernetwork for Continual Learning. WACV 2025: 7298-7307 - [c44]Vishnuprasadh Kumaravelu, P. K. Srijith, Sunil Gupta:
EvoCL: Continual Learning over Evolving Domains. WACV 2025: 7533-7541 - [i23]Lakshmana Sri Harsha Nemani, P. K. Srijith, Tomasz Kusmierczyk:
Efficient Uncertainty in LLMs through Evidential Knowledge Distillation. CoRR abs/2507.18366 (2025) - [i22]Sayanta Adhikari, Vishnuprasadh Kumaravelu, P. K. Srijith:
An Unlearning Framework for Continual Learning. CoRR abs/2509.17530 (2025) - 2024
- [j4]Sai Harsha Yelleni, Deepshikha Kumari, Srijith P. K, Krishna Mohan C:
Monte Carlo DropBlock for modeling uncertainty in object detection. Pattern Recognit. 146: 110003 (2024) - [c43]Vaibhav Shah, Manisha Dubey, Vishnuprasadh Kumaravelu, P. K. Srijith:
Drift-aware Neural Hawkes Process for Time-to-Event Modelling. COMAD/CODS (December) 2024: 160-164 - [c42]Shrey Satapara, P. K. Srijith:
TL-CL: Task And Language Incremental Continual Learning. EMNLP 2024: 12123-12142 - [c41]Debolena Basak, P. K. Srijith, Maunendra Sankar Desarkar:
Transformer based Multitask Learning for Image Captioning and Object Detection. PAKDD (2) 2024: 260-272 - [i21]Debolena Basak, P. K. Srijith, Maunendra Sankar Desarkar:
Transformer based Multitask Learning for Image Captioning and Object Detection. CoRR abs/2403.06292 (2024) - [i20]Dupati Srikar Chandra, P. K. Srijith, Dana Rezazadegan, Chris McCarthy:
Linked Adapters: Linking Past and Future to Present for Effective Continual Learning. CoRR abs/2412.10687 (2024) - 2023
- [c40]Shubham Jain, Srijith P. K:
Monte Carlo Dropout Based BatchEnsemble For Improving Uncertainty Estimation. COMAD/CODS 2023: 138 - [c39]Manisha Dubey, Ragja Palakkadavath, P. K. Srijith:
Event Uncertainty using Ensemble Neural Hawkes Process. COMAD/CODS 2023: 228-232 - [c38]Manisha Dubey, P. K. Srijith, Maunendra Sankar Desarkar:
Time-to-Event Modeling with Hypernetwork based Hawkes Process. KDD 2023: 3956-3965 - [c37]Maunendra Sankar Desarkar Suvodip Dey, Asif Ekbal, P. K. Srijith:
DialoGen: Generalized Long-Range Context Representation for Dialogue Systems. PACLIC 2023: 372-386 - [c36]Srinivas Anumasa, Geetakrishnasai Gunapati, P. K. Srijith:
Continuous Depth Recurrent Neural Differential Equations. ECML/PKDD (2) 2023: 223-238 - [c35]Dupati Srikar Chandra, Sakshi Varshney, P. K. Srijith, Sunil Gupta:
Continual Learning with Dependency Preserving Hypernetworks. WACV 2023: 2338-2347 - 2022
- [j3]R. Gupta, P. K. Srijith, Shantanu Desai:
Galaxy morphology classification using neural ordinary differential equations. Astron. Comput. 38: 100543 (2022) - [j2]Srinadh Reddy Bhavanam, Sumohana S. Channappayya, P. K. Srijith, Shantanu Desai:
Cosmic Ray rejection with attention augmented deep learning. Astron. Comput. 40: 100625 (2022) - [c34]Srinivas Anumasa, P. K. Srijith:
Latent Time Neural Ordinary Differential Equations. AAAI 2022: 6010-6018 - [c33]Srinadh Reddy Bhavanam, Sumohana S. Channappayya, P. K. Srijith, Shantanu Desai:
Cosmic Ray Detection in Astronomical Images via Dictionary Learning and Sparse Representation. EUSIPCO 2022: 1966-1970 - [c32]Sahil Yerawar, Sagar Jinde, P. K. Srijith, Maunendra Sankar Desarkar, K. M. Annervaz, Shubhashis Sengupta:
Predicting Reputation Score of Users in Stack-overflow with Alternate Data. KDIR 2022: 355-362 - [c31]Rohan Tondulkar, Manisha Dubey, P. K. Srijith, Michal Lukasik:
Hawkes Process Classification through Discriminative Modeling of Text. IJCNN 2022: 1-8 - [i19]Dupati Srikar Chandra, Sakshi Varshney, P. K. Srijith, Sunil Gupta:
Continual Learning with Dependency Preserving Hypernetworks. CoRR abs/2209.07712 (2022) - [i18]Manisha Dubey, P. K. Srijith, Maunendra Sankar Desarkar:
HyperHawkes: Hypernetwork based Neural Temporal Point Process. CoRR abs/2210.00213 (2022) - [i17]Suvodip Dey, Maunendra Sankar Desarkar, P. K. Srijith:
Towards Generalized and Explainable Long-Range Context Representation for Dialogue Systems. CoRR abs/2210.06282 (2022) - [i16]Srinivas Anumasa, Geetakrishnasai Gunapati, P. K. Srijith:
Continuous Depth Recurrent Neural Differential Equations. CoRR abs/2212.13714 (2022) - 2021
- [c30]Manisha Dubey, P. K. Srijith, Maunendra Sankar Desarkar:
Multi-view hypergraph convolution network for semantic annotation in LBSNs. ASONAM 2021: 219-227 - [c29]Ragja Palakkadavath, P. K. Srijith:
Bayesian Generative Adversarial Nets with Dropout Inference. COMAD/CODS 2021: 92-100 - [c28]P. Jayashree, Ballijepalli Shreya, P. K. Srijith:
Learning Multi-Sense Word Distributions using Approximate Kullback-Leibler Divergence. COMAD/CODS 2021: 267-271 - [c27]Surya Sai Teja Desu, P. K. Srijith, M. V. Panduranga Rao, Naveen Sivadasan:
Adiabatic Quantum Feature Selection for Sparse Linear Regression. ICCS (6) 2021: 98-112 - [c26]Srinivas Anumasa, P. K. Srijith:
Delay Differential Neural Networks. ICMLT 2021: 117-121 - [c25]Sakshi Varshney, Vinay Kumar Verma, P. K. Srijith, Lawrence Carin, Piyush Rai:
CAM-GAN: Continual Adaptation Modules for Generative Adversarial Networks. NeurIPS 2021: 15175-15187 - [c24]Ayush Jain, P. K. Srijith, Mohammad Emtiyaz Khan:
Subset-of-data variational inference for deep Gaussian-processes regression. UAI 2021: 1362-1370 - [c23]Prashansa Agrawal, A. Antony Franklin, Digvijay S. Pawar, Srijith P. K:
Traffic Incident Duration Prediction using BERT Representation of Text. VTC Fall 2021: 1-5 - [c22]Srinivas Anumasa, P. K. Srijith:
Improving Robustness and Uncertainty Modelling in Neural Ordinary Differential Equations. WACV 2021: 4052-4060 - [i15]Surya Sai Teja Desu, P. K. Srijith, M. V. Panduranga Rao, Naveen Sivadasan:
Adiabatic Quantum Feature Selection for Sparse Linear Regression. CoRR abs/2106.02357 (2021) - [i14]Ayush Jain, P. K. Srijith, Mohammad Emtiyaz Khan:
Subset-of-Data Variational Inference for Deep Gaussian-Processes Regression. CoRR abs/2107.08265 (2021) - [i13]Kumari Deepshikha, Sai Harsha Yelleni, P. K. Srijith, C. Krishna Mohan:
Monte Carlo DropBlock for Modelling Uncertainty in Object Detection. CoRR abs/2108.03614 (2021) - [i12]Srinivas Anumasa, P. K. Srijith:
Improving Robustness and Uncertainty Modelling in Neural Ordinary Differential Equations. CoRR abs/2112.12707 (2021) - [i11]Srinivas Anumasa, P. K. Srijith:
Latent Time Neural Ordinary Differential Equations. CoRR abs/2112.12728 (2021) - [i10]Maunika Tamire, Srinivas Anumasa, P. K. Srijith:
Bi-Directional Recurrent Neural Ordinary Differential Equations for Social Media Text Classification. CoRR abs/2112.12809 (2021) - [i9]Manisha Dubey, Ragja Palakkadavath, P. K. Srijith:
Bayesian Neural Hawkes Process for Event Uncertainty Prediction. CoRR abs/2112.14474 (2021) - 2020
- [c21]Dinesh Jain, Srinivas Anumasa, P. K. Srijith:
Decision Making under Uncertainty with Convolutional Deep Gaussian Processes. COMAD/CODS 2020: 143-151 - [c20]Manisha Dubey, P. K. Srijith, Maunendra Sankar Desarkar:
HAP-SAP: Semantic Annotation in LBSNs using Latent Spatio-Temporal Hawkes Process. SIGSPATIAL/GIS 2020: 377-380 - [c19]Harsh Raj, Suvodip Dey, Hiransh Gupta, P. K. Srijith:
Improving Adaptive Bayesian Optimization with Spectral Mixture Kernel. ICONIP (5) 2020: 370-377 - [c18]Sakshi Varshney, P. K. Srijith, Vineeth N. Balasubramanian:
STM-GAN: Sequentially Trained Multiple Generators for Mitigating Mode Collapse. ICONIP (5) 2020: 676-684 - [c17]P. Jayashree, P. K. Srijith:
Evaluation of Deep Gaussian Processes for Text Classification. LREC 2020: 1485-1491 - [c16]Ankita Likhyani, Vinayak Gupta, Srijith P. K, Deepak P, Srikanta Bedathur:
Modeling Implicit Communities from Geo-Tagged Event Traces Using Spatio-Temporal Point Processes. WISE (1) 2020: 153-169 - [i8]Ankita Likhyani, Vinayak Gupta, Srijith P. K, Deepak P, Srikanta Bedathur:
Modeling Implicit Communities using Spatio-Temporal Point Processes from Geo-tagged Event Traces. CoRR abs/2006.07580 (2020) - [i7]Manisha Dubey, P. K. Srijith, Maunendra Sankar Desarkar:
HAP-SAP: Semantic Annotation in LBSNs using Latent Spatio-Temporal Hawkes Process. CoRR abs/2009.02548 (2020) - [i6]Rohan Tondulkar, Manisha Dubey, P. K. Srijith, Michal Lukasik:
Hawkes Process Classification through Discriminative Modeling of Text. CoRR abs/2010.11851 (2020) - [i5]Srinivas Anumasa, P. K. Srijith:
Delay Differential Neural Networks. CoRR abs/2012.06800 (2020)
2010 – 2019
- 2019
- [c15]Uddipta Bhattacharjee, Srijith P. K, Maunendra Sankar Desarkar:
Term Specific TF-IDF Boosting for Detection of Rumours in Social Networks. COMSNETS 2019: 726-731 - [c14]Uddipta Bhattacharjee, P. K. Srijith, Maunendra Sankar Desarkar:
Leveraging Social Media Towards Understanding Anti-Vaccination Campaigns. COMSNETS 2019: 886-890 - [i4]P. Jayashree, Ballijepalli Shreya, P. K. Srijith:
Learning Multi-Sense Word Distributions using Approximate Kullback-Leibler Divergence. CoRR abs/1911.06118 (2019) - 2018
- [c13]Shamik Kundu, P. K. Srijith, Maunendra Sankar Desarkar:
Classification of Short-Texts Generated During Disasters: A Deep Neural Network Based Approach. ASONAM 2018: 790-793 - [c12]Ashwin Ram, P. K. Srijith:
Accelerating Hawkes process for event history data: Application to social networks and recommendation systems. COMSNETS 2018: 396-399 - [c11]Sherin Thomas, P. K. Srijith, Michal Lukasik:
A Bayesian Point Process Model for User Return Time Prediction in Recommendation Systems. UMAP 2018: 363-364 - [i3]Vinayak Kumar, Vaibhav Singh, P. K. Srijith, Andreas C. Damianou:
Deep Gaussian Processes with Convolutional Kernels. CoRR abs/1806.01655 (2018) - 2017
- [j1]P. K. Srijith, Mark Hepple, Kalina Bontcheva, Daniel Preotiuc-Pietro:
Sub-story detection in Twitter with hierarchical Dirichlet processes. Inf. Process. Manag. 53(4): 989-1003 (2017) - [c10]P. K. Srijith, Michal Lukasik, Kalina Bontcheva, Trevor Cohn:
Longitudinal Modeling of Social Media with Hawkes Process Based on Users and Networks. ASONAM 2017: 195-202 - 2016
- [c9]Michal Lukasik, P. K. Srijith, Duy Vu, Kalina Bontcheva, Arkaitz Zubiaga, Trevor Cohn:
Hawkes Processes for Continuous Time Sequence Classification: an Application to Rumour Stance Classification in Twitter. ACL (2) 2016 - [c8]Daniel Preotiuc-Pietro, P. K. Srijith, Mark Hepple, Trevor Cohn:
Studying the Temporal Dynamics of Word Co-occurrences: An Application to Event Detection. LREC 2016 - [c7]P. K. Srijith, P. Balamurugan, Shirish K. Shevade:
Gaussian Process Pseudo-Likelihood Models for Sequence Labeling. ECML/PKDD (1) 2016: 215-231 - [i2]P. K. Srijith, Mark Hepple, Kalina Bontcheva, Daniel Preotiuc-Pietro:
Sub-Story Detection in Twitter with Hierarchical Dirichlet Processes. CoRR abs/1606.03561 (2016) - 2015
- [c6]Michal Lukasik, P. K. Srijith, Trevor Cohn, Kalina Bontcheva:
Modeling Tweet Arrival Times using Log-Gaussian Cox Processes. EMNLP 2015: 250-255 - 2014
- [c5]P. K. Srijith, Shirish K. Shevade:
Gaussian Process Multi-task Learning Using Joint Feature Selection. ECML/PKDD (3) 2014: 98-113 - [i1]P. K. Srijith, Balamurugan P., Shirish K. Shevade:
Gaussian Process Pseudo-Likelihood Models for Sequence Labeling. CoRR abs/1412.7868 (2014) - 2013
- [c4]P. K. Srijith, Shirish K. Shevade, S. Sundararajan:
Semi-supervised Gaussian Process Ordinal Regression. ECML/PKDD (3) 2013: 144-159 - 2012
- [c3]P. K. Srijith, Shirish K. Shevade, S. Sundararajan:
A Probabilistic Least Squares Approach to Ordinal Regression. Australasian Conference on Artificial Intelligence 2012: 683-694 - [c2]P. K. Srijith, Shirish K. Shevade:
Multi-Task Learning Using Shared and Task Specific Information. ICONIP (3) 2012: 125-132 - [c1]P. K. Srijith, Shirish K. Shevade, S. Sundararajan:
Validation Based Sparse Gaussian Processes for Ordinal Regression. ICONIP (2) 2012: 409-416
Coauthor Index
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