Journals

• Ashwin Srinivasan, A. Baskar, Tirtharaj Dash, Devanshu Shah (2023). Composition of Relational Features with an Application to Explaining Black-Box Predictors, Machine Learning 113(3):1091—1132.
• Tirtharaj Dash, Sharad Chitlanglia, Aditya Ahuja and Ashwin Srinivasan (2022) A review of some techniques for inclusion of domain knowledge into deep neural networks. Nature Scientific Reports 12, 1040.
• Ashwin Srinivasan, Michael Bain and A. Baskar (2022). Learning Explanations for Biological Feedback with Delays in an Event Calculus. Machine Learning, 111(7): 2435–2487
• Tirtharaj Dash, Ashwin Srinivasan an A. Baskar (2022). Inclusion ofDomain-Knowledge into GNNs using Mode-Directed Inverse Entailment. Machine Learning, 111(2): 575–623.
• Tirtharaj Dash, Ashwin Srinivasan and Lovekesh Vig (2021). Incorporating symbolic domain knowledge into graph neural networks, Machine Learning, 110(7): 1609–1636.
• Ashwin Srinivasan, Lovekesh Vig and Gautam Shroff (2020). Constructing Generative Logical Models for Optimisation Problems using Domain Knowledge. Machinr Learning, 109(7): 1371-1392 (2020)
• Ashwin Srinivasan, Lovekesh Vig and Michael Bain (2019). LogicalExplanations for Deep Relational Machines Using Relevance Information. Machine Learning Research. Volume 20, Number 130, pp 1–47

Conferences and Workshops

• Shreyas Bhatt Brahmavar, Ashwin Srinivasan, Tirtharaj Dash, SowmyaKrishnan, Lovekesh Vig, Arijit Roy, Raviprasad Aduri (2024). Generating Novel Leads for Drug Discovery using LLMs with Logical Feedback. AAAI 2024.
• Soham Chitnis, Manasi Patwardhan, Ashwin Srinivasan, Tanmay Tulsidas Verlekar, Lovekesh Vig, Gautam Shroff (2024). AutoRef: Generating Refinements of Reviews Given Guidelines. SDPROC@ACL 2024. Accepted.
• Soham Rohit Chitnis, Sidong Liu, Tirtharaj Dash, Tanmay TulsidasVerlekar, Antonio DiIeva, Shlomo Berkovsky, Lovekesh Vig, Ashwin Srinivasan (2023). Domain-Specific Pre-training Improves Confidence in Whole Slide Image Classification. EMBC 2023: 1–4.
• Shreyas Bhat Brahmavar, Rohit Rajesh, Tirtharaj Dash, LovekeshVig, Tanmay Tulsidas Verlekar, Md Mahmudul Hasan, Tariq Mahmood Khan, Erik Meijering, Ashwin Srinivasan (2023). IKD+: Reliable Low Complexity
• Shrey Pandit, Gautam Shroff, Ashwin Srinivasan, Lovekesh Vig (2023). Can LLMs solve generative visual analogies? IARML@IJCAI 2023: 30-32
• Vishwa Shah, Aditya Sharma, Gautam Shroff, Lovekesh Vig, TirtharajDash, Ashwin Srinivasan (2022). Knowledge-based Analogical Reasoning in Neuro-symbolic Latent Spaces. NeSy@IJCLR 2022: 142-154.
• Tirtharaj Dash, Ashwin Srinivasan, Lovekesh Vig, Arijit Roy (2021). Using Domain-Knowledge to Assist Lead Discovery in Early-Stage Drug Design, 30^th International Conference on Inductive Logic Programming.
• Het Shah, Ashwin Vaswani, Tirtharaj Dash, Ramya Hebbalaguppe,Ashwin Srinivasan (2021). Empirical Study of Data-Free Iterative Knowledge Distillation. ICANN (3) 2021: 546-557.
• Sanket Rajan Gupte, Dharm Skandh Jain, Ashwin Srinivasan, Raviprasad Aduri (2020). MP3vec: A Reusable Machine-Constructed Feature Representation for Protein Sequences. BIBM 2020: 421-425
• Mouli Rastogi, Syed Afshan Ali, Mrinal Rawat, Lovekesh Vig, PuneetAgarwal, Gautam Shroff, Ashwin Srinivasan (2020) Information Extraction from Document Images via FCA based Template Detection and Knowledge Graph Rule Induction. CVPR Workshops 2020: 23772385
• Sharan Yalburgi, Tirtharaj Dash, Ramya Hebbalaguppe, Srinidhi Hegde,Ashwin Srinivasan (2020). An Empirical Study of Iterative Knowledge Distillation for Neural Network Compression. ESANN 2020: 217-222
• Kushagra Mahajan, Monika Sharma, Lovekesh Vig, Rishab Khincha,Soundarya Krishnan, Adithya Niranjan, Tirtharaj Dash, Ashwin Srinivasan, Gautam Shroff (2020). CovidDiagnosis: Deep Diagnosis of COVID-19 Patients Using Chest X-Rays. TIA@MICCAI 2020: 6173
• Soundarya Krishnan, Rishab Khincha, Lovekesh Vig, Tirtharaj Dash,Ashwin Srinivasan: A Case Study of Transfer of Lesion-Knowledge. iMIMIC/MIL3ID/LABELS@MICCAI 2020: 138-145
• Richa Verma, Sarmimala Saikia, Harshad Khadilkar, Puneet Agarwal, Gautam Shroff, Ashwin Srinivasan (2019). A Reinforcement Learning Framework for Container Selection and Ship Load Sequencing in Ports. AAMAS 2019: 2250-2252.