Technical Reports

  1. AmalREC: A Dataset for Relation Extraction and Classification Leveraging Amalgamation of Large Language Models. Mansi, Pranshu Pandya, Mahek Bhavesh Vora, Soumya Bharadwaj, Ashish Anand. 2024. arXiv
  2. A Generative Marker Enhanced End-to-End Framework for Argument Mining. Nilmadhab Das, Vishal Choudhary, V. Vijaya Saradhi, Ashish Anand. 2024. arXiv
  3. Enhancing Event Extraction from Short Stories through Contextualized Prompts. Chaitanya Kirti, Ayon Chattopadhyay, Ashish Anand, and Prithwijit Guha. 2024 arXiv
  4. Inference of splicing motifs through visualization of recurrent networks. Aparajita Dutta, Aman Dalmia, Athul R, Kusum Kumari Singh, Ashish Anand. 2018. biorXiv:451906
  5. Unified Neural Architecture for Drug, Disease and Clinical Entity Recognition. Sunil Kumar Sahu, Ashish Anand. 2017. arXiv:1708.03447
  6. Inferring disease correlation from healthcare data. Priyadarshini G, Anand A. 2015. arXiv:1510.03051[cs.IR]

Journals

  1. C. Kirti, Ashish Anand, P.Guha, "Exploring Neural and Prompt-Based Approaches for Event Detection in Short Stories", International Journal of Asian Language Processing, (Accepted in June, 2024) Publisher's site  
  2. A Mishra, Ashish Anand , and P Guha, "Dual Attention and Question Categorization based Visual Question Answering", IEEE Transactions on Artificial Intelligence, (Accepted in March, 2022) Publisher's site  
  3. M Paul, and Ashish Anand . "A New Family of Similarity Measures for Scoring Confidence of Protein Interactions using Gene Ontology." IEEE/ACM Transactions on Computational Biology and Bioinformatics, 19(1), January/February 2022, 19--30. DOI
  4. A Dutta, K K Singh, and Ashish Anand . "SpliceViNCI: Visualizing the splicing of non-canonical introns through recurrent neural networks." Journal of Bioinformatics and Computational Biology (Accepted: May, 2021; In Press). Preprint DOI
  5. M Paul, and Ashish Anand . "Impact of low-confidence interactions on computational identification of protein complexes." Journal of Bioinformatics and Computational Biology (In Press).
  6. A Dutta, A Dalmia, R. Athul, K K Singh, and Ashish Anand . "Using the Chou’s 5-steps rule to predict splice junctions with interpretable bidirectional long short-term memory networks." Computers in Biology and Medicine (2019). Publisher's site   Preprint 
  7. S Pyne, Ashish Anand. "Rapid Reconstruction of Time-varying Gene Regulatory Networks with Limited Main Memory". IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2019, In press. Publisher's site   Preprint  Code & data
  8. S Pyne, Ashish Anand. "Rapid Reconstruction of Time-varying Gene Regulatory Networks". IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2018, In press. Publisher's site   Preprint  Code & data
  9. S K Sahu, Ashish Anand. Drug-Drug Interaction Extraction from Biomedical Text Using Long Short Term Memory Network. 2018. Vol 86: 15-24. Publisher's site   Preprint 
  10. S K Sahu, Ashish Anand. What matters in a transferable neural network model for relation classification in the biomedical domain? Artificial Intelligence in Medicine, 2018, Vol 87: 60-66. Publisher's site
  11. A Dutta, T Dubey, K K Singh, Ashish Anand. SpliceVec: Distributed feature representations for splice junction prediction. Computational Biology and Chemistry, 2018, Vol 74: 434-441. Publisher's site
  12. M Paul, R Anand, Ashish Anand. Detection of Highly Overlapping Communities in Complex Networks. Journal of Medical Imaging and Health Informatics, 2015, Vol 5(5), 1099-1103.
  13. Ashish Anand, G Pugalenthi, G B Fogel, And P N Suganthan. An approach for classification of highly imbalanced data using weighting and undersampling. Amino Acids, 2010, Vol 39(5), 1385-1391
  14. Ashish Anand, G Pugalenthi, G B Fogel, and P N Suganthan. Identification and analysis of transcription factor family-specific features derived from DNA and protein information. Pattern Recognition Letters, 2010, Vol 31(14), 2097-2102
  15. Ashish Anand, P N Suganthan. Multiclass cancer classification by support vector machines with class-wise optimized genes and probability estimates. Journal of Theoretical Biology, 2009, Vol 259(3), 533-540
  16. Ashish Anand, G Pugalenthi, P N Suganthan. Predicting protein structural class by SVM with class-wise optimized features and decision probabilities. Journal of Theoretical Biology, 2008, Vol 253(2), 375-380
  17. H Santti H, L Mikkonen, Ashish Anand; et al. Disruption of the murine PIASx gene results in reduced testis weight. Journal of Molecular Endocrinology, 2005, Vol 34(3), 645-654
  18. K Deb, Ashish Anand, D. Joshi. A computationally efficient evolutionary algorithm for real-parameter optimization. Evolutionary Computation, 2002, Vol 10(4), 371-395

Conferences

  1. Nilmadhab Das, V. Vijaya Saradhi, Ashish Anand. 2025. On the Role of Key Phrases in Argument Mining. In Findings of NAACL 2025, New Mexico. [Openreview Annonymous Pre-Print]
  2. Nazreena Rahman, Pankaj Choudhury, Prithwijit Guha, Ashish Anand and Sukumar Nandi. 2024. TDIUC-AVQA: A Visual Question Answering Dataset in Low-Resource Assamese Language. In Proceedings of CVIP 2024, India. [Publisher Site]
  3. Aakansha Mishra, Ashish Anand, P.Guha. 2024. Visual Question Answering with Cascade of Self- and Co-Attention Blocks. In Proceedings of ICPR 2024, India. [Publisher Site]
  4. C. Kirti, P. Choudhury, Ashish Anand, P.Guha. 2023. An Annotated Corpus for Realis Event Detection in Short Stories Written in English and Low Resource Assamese Language. In Proceedings of ICON 2023, India. [Publisher Site]
  5. A. Mishra, Ashish Anand, P.Guha. 2023. Aggregated Co-attention based Visual Question Answering. In Proceedings of ICVGIP 2023, India. [Publisher Site]
  6. C. Kirti, A. Chattopadhyay, Ashish Anand, P.Guha. 2023. Deciphering Storytelling Events: A Study of Neural and Prompt-Driven Event Detection in Short Stories. In Proceedings of IALP 2023, Singapore. [Publisher Site]
  7. A Prabhakar, G S Majumder, Ashish Anand. 2022. CL-NERIL: A cross-lingual model for NER in Indian Languages. In Proceedings of AAAI 2022, Vancouver, Canada. [Publisher Site]
  8. V Goel, M Chandak, Ashish Anand and P Guha. 2021. IQ-VQA: Intelligent Visual Question. in Proceedings of International Conference on Pattern Recognition, ICPR Workshop 2020-2021, Italy. [Publisher Site]
  9. A Mishra, Ashish Anand, and P Guha. 2020-2021. Multi-stage Attention based Visual Question Answering. in Proceedings of International Conference on Pattern Recognition, ICPR 2021, Italy. [Publisher Site]
  10. M Paul, Ashish Anand. "A New Family of Similarity Measures for Scoring Confidence of Protein Interactions using Gene Ontology". Asia Pacific Bioinformatics Conference (APBC), Taiwan. 2021.
  11. S Basu, S Chakraborty, A Hassan, S Siddique, Ashish Anand. ERLKG: Entity Representation Learning and Knowledge Graph based association analysis of COVID-19 through mining of unstructured biomedical corpora. In Proceedings of EMNLP Workshop on Scholarly Document Processing 2020. [Publisher Site]
  12. A Mishra, Ashish Anand, and P Guha. 2020. CQ-VQA: Visual Question Answering on Categorized Questions. in Proceedings of International Joint Conference on Neural Networks 2020, Glasgow, UK. (WCCI - IJCNN 2020). [PDF]
  13. A Parekh, Ashish Anand, and Amit Awekar. 2020. Taxonomical hierarchy of canonicalized relations from multiple Knowledge Bases. In 7th ACM IKDD CoDS and 25th COMAD (CoDS COMAD 2020), January 5–7,2020, Hyderabad, India. [PDF]
  14. M Paul, Ashish Anand and S Pyne. Impact of the Continuous Evolution of Gene Ontology on Similarity Measures. Presented in Pattern Recognition and Machine Intelligence (PReMI) 2019, Tezpur, India. Published in Lecture Notes in Computer Science, vol. 11942, pp. 122-129, Springer. Publisher's site
  15. Abhishek, A P Azad, B Ganesan, Ashish Anand, A Awekar. Collective Learning From Diverse Datasets for Entity Typing in the Wild. 2nd International Workshop on Entity Retrieval (EYRE), CIKM 2019. [ PDF ]
  16. Abhishek, Sanya B Taneja, Garima Malik, Ashish Anand, Amit Awekar. Fine-grained Entity Recognition with Reduced False Negatives and Large Type Coverage. Accepted in AKBC 2019, USA. [ PDF]
  17. V Agarwal, N Jayanth K Reddy, Ashish Anand. Unsupervised Representation Learning for DNA sequences. In Proceedings of Workshop on Computational Biology, ICML 2019. [ PDF ]
  18. V M Malhotra, Ashish Anand}. Teaching a University-Wide Programming Laboratory: Managing a C Programming Laboratory for a Large Class with Diverse Interests. 2019. ACE '19 Proceedings of the Twenty-First Australasian Computing Education Conference 2019.
  19. A Dutta, T Dubey, K K Singh, Ashish Anand. SpliceVec: distributed feature representations for splice junction prediction. Accepted in APBC 2018, Japan. [ PDF ]
  20. D Raj, S K Sahu, Ashish Anand. Learning local and global contexts using a convolutional recurrent network model for relation classication in biomedical text. Accepted in CoNLL 2017, Canada. [ PDF ]
  21. Rahul, S K Sahu, Ashish Anand. Biomedical Event Trigger Identification Using Recurrent Neural Network. In proceeding of ACL-BioNLP 2017, Canada. [ PDF ]
  22. S Manchanda, Ashish Anand. Representation learning of drug and disease terms for drug repositioning. Accepted in In proceeding of 3rd IEEE International Conference on Cybernetics 2017.[ PDF ]
  23. Abhishek, Ashish Anand and A Awekar. Fine-Grained Entity Type Classification by Jointly Learning Representations and Label Embeddings. Accepted in EACL 2017, Spain (Long Paper). [ PDF ]
  24. S K Sahu, Ashish Anand, K Oruganty and M Gattu. Relation extraction from clinical texts using domain invariant convolutional neural network. Accepted in ACL BioNLP 2016, Germany. [ PDF ]
  25. S K Sahu, Ashish Anand. Recurrent neural network models for disease name recognition using domain invariant features. Accepted in ACL 2016, Germany (Long) paper. [ PDF ] (Sunil acknowledges the travel grants from Google and Microsoft for presenting the paper in the conference.)
  26. Muneeb TH, S K Sahu, Ashish Anand. Evaluating distributed word representations for capturing semantics of biomedical concepts. Inproceedings of the ACL-BioNLP 2015 workshop, Beijing China. [ PDF ]
  27. M Paul, R Anand, Ashish Anand. Detection of Highly Overlapping Communities in Complex Networks. 5th International Conference on Computational Systems-Biology and Bioinformatics 2014, Singapore.
  28. G Priyadarshini, Ashish Anand. Inferring Disease Correlation from Healthcare Data, National Conference on Medical Informatics.2014. AIIMS, New Delhi
  29. Ashish Anand, N R Pal, P N Suganthan. Integration of Functional Information of Genes in Fuzzy Clustering of Short Time Series Gene Expression Data. In: Proceeding of IEEE World Congress on Computational Intelligence 2010, Barcelona, Spain
  30. Ashish Anand, G B Fogel, G Pugalenthi, P N Sunagnthan. Prediction of Transcription Factor Families Using DNA Sequence Features. In: Proceedings of Pattern Recognition in Bioinformatics 2008, Melbourne, Australia
  31. Ashish Anand, P N Suganthan, K Deb. A novel fuzzy and multiobjective evolutionary algorithm based gene assignment for clustering short time series expression data.In: IEEE Congress on Evolutionary Computation 2007, Vols 1-10, Pages: 297-304
  32. Ashish Anand, G B Fogel, E K Tang, P N Suganthan. Feature selection approach for quantitative prediction of transcriptional activities. Computational Intelligence and Bioinformatics and Computational Biology IEEE Symposium on, 2006.
  33. K Deb, D Joshi, Ashish Anand. Real-coded evolutionary algorithms with parent-centric recombination. In: Proceedings of the 2002 IEEE Congress on Evolutionary Computation, Hawaii

Book Chapters

  1. Unified neural architecture for drug, disease, and clinical entity recognition. SK Sahu, Ashish Anand. Deep Learning Techniques for Biomedical and Health Informatics, 1-19, 2020. Publisher's site
  2. Feature selection using Rough Set. M Banerjee, S Mitra, A Anand. Multiobjective machine lerarning (Eds Dr Yaochu Jin), Springer-Verlag 2006

Posters

  1. Towards Genome-scale Disease Progression Modeling. Saptarshi Pyne, Alok R Kumar, Anand A. 17th International Conference on Bioinformatics (InCoB) 2018, New Delhi, India.
  2. Multi-label classification with label clustering. Pranav Gupta, Anand A. 1st Indian workshop on Machine Learning, IIT Kanpur India.
  3. A software architecture for de Novo induction of regulatory network from expression data. Ruegheimer F, Anand A, Schwikowski B. In: Proceedings of JOBIM 2011, Paris, France.
  4. Inferring a latent regulation network for Bacillus subtilis using a kernel matrix completion approach. Ashish Anand, S Drulhe, F Gwinner, F Ruegheimer, P Bochet, B Schwikowski. 11th International Conference on Systems Biology, ICSB, 2010, Edinburgh.