Publications

Sai Harsha Yelleni, Deepshikha Kumari, Srijith P.K., Krishna Mohan C., Monte Carlo DropBlock for modeling uncertainty in object detection, Pattern Recognition, 2024.
S Anumasa, G Gunapati, P. K. Srijith, Continuous Depth Recurrent Neural Differential Equations, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), 2023.
Manisha Dubey, P.K. Srijith and Maunendra Sankar Desarkar, Time-to-Event Modeling with Hypernetwork based Hawkes Process, 29th ACM SIGKDD conference on knowledge discovery and data mining (KDD), 2023.
Dubey, Manisha & Palakkadavath, Ragja & Srijith, P. K. Bayesian neural Hawkes process for event uncertainty prediction. International Journal of Data Science and Analytics. 1-15. 2023.
Manisha Dubey, Ragja Palakkadavath, P. K. Srijith: Event Uncertainty using Ensemble Neural Hawkes Process. Conference on Data Sciences (CoDS) 2023.
Srikar Dupati, Sakshi Varshney, P.K. Srijith, Sunil, Gupta, Continual Learning with Dependency Preserving Hypernetworks, IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 2023.
Srinivas Anumasa and P. K. Srijith, Latent Time Neural Ordinary Differential Equations, Proceedings of the Association for the Advancement of Artificial Intelligence (AAAI), 36 (6), pp 6010-6018, 2022.
Maunika Tamire, Srinivas Anumasa, and P. K. Srijith. 2022. Bi-Directional Recurrent Neural Ordinary Differential Equations for Social Media Text Classification. In Proceedings of the 2nd Workshop on Deriving Insights from User-Generated Text, pages 20–24, Association for Computational Linguistics (ACL), 2022.
Rohan Tondulkar, Manisha Dubey, PK Srijith, Michal Lukasik, Hawkes Process Classification through Discriminative Modeling of Text, International Joint Conference on Neural Networks (IJCNN), 2022
R. Gupta, P.K. Srijith, S. Desai, Galaxy morphology classification using neural ordinary differential equations, Astronomy and Computing 38 , 2022.
Srinadh Reddy Bhavanam, Sumohana S. Channappayya, P. K. Srijith, Shantanu Desai: Cosmic Ray rejection with attention augmented deep learning. Astron. Comput. 40: 100625 (2022)
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. Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (KDIR), 2022.
G Gunapati, A Jain, P. K. Srijith, S Desai, Variational inference as an alternative to mcmc for parameter estimation and model selection, Publications of the Astronomical Society of Australia 39, 2022.
A Bhave, S Kulkarni, S Desai, PK Srijith, Two dimensional clustering of Gamma-Ray Bursts using durations and hardness, Astrophysics and Space Science 367 (4), 1-10, 2022.
Sakshi Varshney, Vinay Kumar Verma, P. K. Srijith, Lawrence Carin, Piyush Rai: CAM-GAN: Continual Adaptation Modules for Generative Adversarial Networks, Neural Information Processing Systems ( NeurIPS ), 2021
Manisha Dubey, P.K. Srijith and Maunendra Sankar Desarkar. Multi-view Hypergraph Convolution Network for Semantic Annotation in LBSNs , IEEE/ACM International Conference on Advances in Social Network Analysis and Mining (ASONAM), 2021.
Ayush Jain, P. K. Srijith, and M. E. Khan, Subset-of-Data Variational Inference for Deep Gaussian-Processes Regression, Uncertainty in Artificial Intelligence (UAI), 2021
Surya Sai Teja Desu, P.K. Srijith, M.V. Panduranga Rao , and Naveen Sivadasan; Adiabatic Quantum Feature Selection for Sparse Linear Regression, International Conference on Computational Science (ICCS) 2021.
P Agrawal, A Franklin, D Pawar, P. K. Srijith, Traffic Incident Duration Prediction using BERT Representation of Text, IEEE 94th Vehicular Technology Conference, 1-5, 2021.
Srinivas Anumasa and P. K. Srijith, Delay Differential Neural Networks , International Conference on Machine Learning Technologies (ICMLT), 2021.
Srinivas Anumasa and P. K. Srijith, Improving Robustness and Uncertainty modelling in Neural Ordinary Differential Equations, IEEE Winter Conference on Applications of Computer Vision ( WACV) 2021.
Ragja Palakkadavath and P.K. Srijith, Bayesian Generative Adversarial Nets with Dropout Inference, International Conference on Data Sciences (CODS) 2021.
P. Jayashree, Ballijepalli Shreya and P.K. Srijith, Learning Multi-Sense Word Distributions using Approximate Kullback-Leibler Divergence, International Conference on Data Sciences ( CODS ) 2021.
M Dubey, PK Srijith, MS Desarkar. HAP-SAP: Semantic Annotation in LBSNs using Latent Spatio-Temporal Hawkes Process. Proceedings of the 28th International Conference on Advances in Geographic Information Systems (SIGSPATIAL), 2020.
A Likhyani, V Gupta, PK Srijith, P Deepak, S Bedathur. Modeling Implicit Communities from Geo-Tagged Event Traces Using Spatio-Temporal Point Processes International Conference on Web Information Systems Engineering (WISE), 2020.
Harsh Raj, Suvodip Dey, Hiransh Gupta, and P.K. Srijith. Improving Adaptive Bayesian Optimization with Spectral Mixture Kernel, International Conference on Neural Information Processing (ICONIP), 2020.
Sakshi Varshney, P. K. Srijith, Vineeth N Balasubramanian. STM-GAN: Sequentially Trained Multiple Generators for Mitigating Mode Collapse, International Conference on Neural Information Processing (ICONIP), 2020.
P Jayashree, PK Srijith. Evaluation of Deep Gaussian Processes for Text Classification. Proceedings of The 12th Language Resources and Evaluation Conference (LREC), 2020.
Jain, D., Anumasa, S., & Srijith, P. K. Decision making under uncertainty with convolutional deep Gaussian processes. In ACM International Conference on Data Sciences. CODS 2020.
Tondulkar, R., Srijith, P.K. & Lukasik, M. Stance classification using discriminative modelling of text in Hawkes process, Temporal Point Process workshop, Neural Information Processing Systems (NeurIPS), December 2019.
Bhattacharjee, U., Srijith, P. K., & Desarkar, M. S. (2019). Term Specific TF-IDF Boosting for Detection of Rumours in Social Networks. In 2019 11th International Conference on Communication Systems and Networks, COMSNETS 2019.
Bhattacharjee, U., Srijith, P. K., & Desarkar, M. S. (2019). Leveraging Social Media Towards Understanding Anti-Vaccination Campaigns. In 2019 11th International Conference on Communication Systems and Networks, COMSNETS 2019.
Vinayak Kumar, Vaibhav Singh, P. K. Srijith, Andreas Damianou, Deep Gaussian Processes with Convolutional Kernels, Uncertainty in Deep Learning workshop at Uncertainty in Artificial Intelligence (UAI), 2018
Sherin Thomas, P. K. Srijith, and Michal Lukasik. 2018. A Bayesian Point Process Model for User Return Time Prediction in Recommendation Systems. In User Modeling, Adaptation and Personalization (UMAP), 2018
Shamik Kundu, P.K. Srijith, M. S. Desarkar. Classification of Short-Texts Generated During Disasters: A Deep Neural Network Based Approach. In FOSINT-SI at Advances in Social Networks Analysis and Mining (ASONAM) 2018.
Ashwin R. Ravi, P. K. Srijith, Accelerating Hawkes Process for Modelling Event History Data, Time Series Workshop, ICML, 2017 (also on COMSNETS 2018).
P. K. Srijith, Michal, Lukasik, Kalina, Bontcheva, and Trevor, Cohn, Longitudinal Modeling of Social Media with Hawkes Process based on Users and Networks. IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2017.
P.K.,Srijith,Hepple,M.,Bontcheva,K.,Preoutiuc,D., Substory detection in Twitter using Hierarchical Dirichlet processes. Information Processing and Management (IPM), 2017.
Samujjwal Ghosh, Srijith P. K., and M. S. Desarkar: Using Social Media for Classifying Actionable Insights in Disaster Scenario. International Journal of Advances in Engineering Sciences (Springer), December 2017.
P. K., Srijith, P., Balamuraugan, Shevade, S.: Gaussian Process Pseudo-Likelihood Models for Sequence Labeling, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD) , 2016.
M., Lukasik, P.K., Srijith, T.,Cohn, D.,Vu, K., Bontcheva, Hawkes Processes for Continuous Time Sequence Classification: Application for Stance Classification in Twitter, Association of Computational Linguistics (ACL), 2016.
Preoutiuc, D., P. K., Srijith, Hepple, M., Cohn, T., Studying the temporal dynamics of word co-occurrences: An application to event detection, Language Resource and Evaluation (LREC), 2016.
Michal Lukasik, P.K. Srijith, Trevor Cohn and Kalina Bontcheva. Modeling Tweet Arrival Times using Log-Gaussian Cox Processes. Empirical Methods of Natural Language Processing (EMNLP), 2015.
P.K., Srijith, P., Balamuraugan, Shevade, S.: Efficient Variational Inference for Gaussian Process Structured Prediction., Advances in Variational Inference workshop, Neural Information Processing Systems (NIPS), 2014
P. K., Srijith, Shirish, S.: Gaussian Process Multi-task Learning Using Joint Feature Selection. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), 2014
P.K., Srijith, Shevade, S., Sundararajan, S.: Semi-supervised Gaussian Process Ordinal Regression. , European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD) , 2013
P.K., Srijith, Shevade, S., Sundararajan, S.: Validation-Based Sparse Gaussian Processes for Ordinal Regression. International Conference on Neural Information Processing (ICONIP), 2012
P.K., Srijith, Shevade, S.: Multi-task Learning using Shared and Task Specific Information. International Conference on Neural Information Processing (ICONIP), 2012
P.K., Srijith, Shevade, S., Sundararajan, S.: A Probabilistic Least Squares approach to Ordinal Regression, 25th Australasian Joint Conference on Artificial Intelligence (AI), 2012

Preprints

Kumari Deepshikha, Sai Harsha Yelleni, P. K. Srijith and C. Krishna Mohan, Monte Carlo DropBlock for Modelling Uncertainty in Object Detection, arXiv preprint abs/2108.03614, 2021.
S Anumasa, PK Srijith, Delay Differential Neural Networks , arXiv preprint arXiv:2012.06800, 2020
R Tondulkar, M Dubey, PK Srijith, M Lukasik, Hawkes Process Classification through Discriminative Modeling of Text, arXiv preprint arXiv:2010.11851, 2020
V Kumar, V Singh, PK Srijith, A Damianou, Deep Gaussian Processes with Convolutional Kernels, arXiv preprint arXiv:1806.01655, 2018.
A Jain, PK Srijith, S Desai, Variational Inference as an alternative to MCMC for parameter estimation and model selection in Astrophysics, arXiv preprint arXiv:1803.06473, 2018.