Compression, Significance, and Accuracy. - Stephen H. Muggleton; Ashwin Srinivasan 001; Michael Bain 001 (ML, 1992)

The Justification of Logical Theories based on Data Compression. - Ashwin Srinivasan 001; Stephen H. Muggleton; Michael Bain 001 (Machine Intelligence 13, 1992)

Ripple down rules: Turning knowledge acquisition into knowledge maintenance. - Paul Compton; Glenn Edwards; Byeong Kang 001; Leslie Lazarus; Ron Malor; Phillip Preston; Ashwin Srinivasan 001 (Artif. Intell. Medicine, 1992)

Generating Explicit Orderings for Non-monotonic Logics. - James Cussens; Anthony Hunter; Ashwin Srinivasan 001 (AAAI, 1993)

Inductive Logic Programming With Large-Scale Unstructured Data. - Michael Bain 001; Ashwin Srinivasan 001 (Machine Intelligence 14, 1993)

Drug Design by Machine Learning. - Michael J. E. Sternberg; Ross D. King; Ashwin Srinivasan 001; Stephen H. Muggleton (Machine Intelligence 15, 1995)

Relating Chemical Activity to Structure: An Examination of ILP Successes. - Ross D. King; Michael J. E. Sternberg; Ashwin Srinivasan 001 (New Gener. Comput., 1995)

An Initial Experiment into Stereochemistry-Based Drug Design Using Inductive Logic Programming. - Stephen H. Muggleton; David Page; Ashwin Srinivasan 001 (Inductive Logic Programming Workshop, 1996)

Feature Construction with Inductive Logic Programming: A Study of Quantitative Predictions of Biological Activity by Structural Attributes. - Ashwin Srinivasan 001; Ross D. King (Inductive Logic Programming Workshop, 1996)

Theories for Mutagenicity: A Study in First-Order and Feature-Based Induction. - Ashwin Srinivasan 001; Stephen H. Muggleton; Michael J. E. Sternberg; Ross D. King (Artif. Intell., 1996)

The Predictive Toxicology Evaluation Challenge. - Ashwin Srinivasan 001; Ross D. King; Stephen H. Muggleton; Michael J. E. Sternberg (IJCAI (1), 1997)

Carcinogenesis Predictions Using ILP. - Ashwin Srinivasan 001; Ross D. King; Stephen H. Muggleton; Michael J. E. Sternberg (ILP, 1997)

The discovery of indicator variables for QSAR using inductive logic programming. - Ross D. King; Ashwin Srinivasan 001 (J. Comput. Aided Mol. Des., 1997)

Biochemical Knowledge Discovery Using Inductive Logic Programming. - Stephen H. Muggleton; Ashwin Srinivasan 001; Ross D. King; Michael J. E. Sternberg (Discovery Science, 1998)

Application of ILP to Problems in Chemistry and Biology (Abstract). - Ashwin Srinivasan 001 (ILP, 1998)

Pharmacophore Discovery Using the Inductive Logic Programming System PROGOL. - Paul W. Finn; Stephen H. Muggleton; David Page; Ashwin Srinivasan 001 (Mach. Learn., 1998)

An assessment of submissions made to the Predictive Toxicology Evaluation Challenge. - Ashwin Srinivasan 001; Ross D. King; Douglas W. Bristol (IJCAI, 1999)

An Assessment of ILP-Assisted Models for Toxicology and the PTE-3 Experiment. - Ashwin Srinivasan 001; Ross D. King; Douglas W. Bristol (ILP, 1999)

A Study of Two Sampling Methods for Analyzing Large Datasets with ILP. - Ashwin Srinivasan 001 (Data Min. Knowl. Discov., 1999)

Feature Construction with Inductive Logic Programming: A Study of Quantitative Predictions of Biological Activity Aided by Structural Attributes. - Ashwin Srinivasan 001; Ross D. King (Data Min. Knowl. Discov., 1999)

Numerical Reasoning with an ILP System Capable of Lazy Evaluation and Customised Search. - Ashwin Srinivasan 001; Rui Camacho (J. Log. Program., 1999)

Measuring Performance when Positives Are Rare: Relative Advantage versus Predictive Accuracy - A Biological Case Study. - Stephen H. Muggleton; Christopher H. Bryant; Ashwin Srinivasan 001 (ECML, 2000)

Learning Chomsky-like Grammars for Biological Sequence Families. - Stephen H. Muggleton; Christopher H. Bryant; Ashwin Srinivasan 001 (ICML, 2000)

Discovering the Structure of Partial Differential Equations from Example Behaviour. - Ljupco Todorovski; Saso Dzeroski; Ashwin Srinivasan 001; Jonathan P. Whiteley; David Gavaghan (ICML, 2000)

A Note on Two Simple Transformations for Improving the Efficiency of an ILP System. - Vítor Santos Costa; Ashwin Srinivasan 001; Rui Camacho (ILP, 2000)

The Predictive Toxicology Challenge 2000-2001. - Christoph Helma; Ross D. King; Stefan Kramer 001; Ashwin Srinivasan 001 (Bioinform., 2001)

Classificatory challenge-data mining: a recipe. - Steve Moyle; Ashwin Srinivasan 001 (Informatica (Slovenia), 2001)

Warmr: a data mining tool for chemical data. - Ross D. King; Ashwin Srinivasan 001; Luc Dehaspe (J. Comput. Aided Mol. Des., 2001)

Are Grammatical Representations Useful for Learning from Biological Sequence Data? - A Case Study. - Stephen H. Muggleton; Christopher H. Bryant; Ashwin Srinivasan 001; Alex Whittaker; Simon Topp; Christopher J. Rawlings (J. Comput. Biol., 2001)

Extracting Context-Sensitive Models in Inductive Logic Programming. - Ashwin Srinivasan 001 (Mach. Learn., 2001)

The Applicability to ILP of Results Concerning the Ordering of Binomial Populations. - Ashwin Srinivasan 001 (ILP, 2002)

Lattice-Search Runtime Distributions May Be Heavy-Tailed. - Filip Zelezný; Ashwin Srinivasan 001; David Page (ILP, 2002)

Statistical Evaluation of the Predictive Toxicology Challenge 2000-2001. - Hannu Toivonen; Ashwin Srinivasan 001; Ross D. King; Stefan Kramer 001; Christoph Helma (Bioinform., 2003)

Query Transformations for Improving the Efficiency of ILP Systems. - Vítor Santos Costa; Ashwin Srinivasan 001; Rui Camacho; Hendrik Blockeel; Bart Demoen; Gerda Janssens; Jan Struyf; Henk Vandecasteele; Wim Van Laer (J. Mach. Learn. Res., 2003)

ILP: A Short Look Back and a Longer Look Forward. - David Page; Ashwin Srinivasan 001 (J. Mach. Learn. Res., 2003)

An Empirical Study of the Use of Relevance Information in Inductive Logic Programming. - Ashwin Srinivasan 001; Ross D. King; Michael Bain 001 (J. Mach. Learn. Res., 2003)

A Monte Carlo Study of Randomised Restarted Search in ILP. - Filip Zelezný; Ashwin Srinivasan 001; David Page (ILP, 2004)

Multi-instance tree learning. - Hendrik Blockeel; David Page; Ashwin Srinivasan 001 (ICML, 2005)

Five Problems in Five Areas for Five Years. - Ashwin Srinivasan 001 (ILP, 2005)

A Study of Applying Dimensionality Reduction to Restrict the Size of a Hypothesis Space. - Ashwin Srinivasan 001; Ravi Kothari (ILP, 2005)

ILP Through Propositionalization and Stochastic k-Term DNF Learning. - Aline Paes; Filip Zelezný; Gerson Zaverucha; C. David Page Jr.; Ashwin Srinivasan 001 (ILP, 2006)

Word Sense Disambiguation Using Inductive Logic Programming. - Lucia Specia; Ashwin Srinivasan 001; Ganesh Ramakrishnan; Maria das Graças Volpe Nunes (ILP, 2006)

Guest editorial. - Rui Camacho; Ross D. King; Ashwin Srinivasan 001 (Mach. Learn., 2006)

Quantitative pharmacophore models with inductive logic programming. - Ashwin Srinivasan 001; David Page; Rui Camacho; Ross D. King (Mach. Learn., 2006)

Randomised restarted search in ILP. - Filip Zelezný; Ashwin Srinivasan 001; C. David Page Jr. (Mach. Learn., 2006)

Learning Qualitative Models of Physical and Biological Systems. - Simon M. Garrett; George Macleod Coghill; Ashwin Srinivasan 001; Ross D. King (Computational Discovery of Scientific Knowledge, 2007)

Using ILP to Construct Features for Information Extraction from Semi-structured Text. - Ganesh Ramakrishnan; Sachindra Joshi; Sreeram Balakrishnan; Ashwin Srinivasan 001 (ILP, 2007)

USP-IBM-1 and USP-IBM-2: The ILP-based Systems for Lexical Sample WSD in SemEval-2007. - Lucia Specia; Maria das Graças Volpe Nunes; Ashwin Srinivasan 001; Ganesh Ramakrishnan (SemEval@ACL, 2007)

Feature Construction Using Theory-Guided Sampling and Randomised Search. - Sachindra Joshi; Ganesh Ramakrishnan; Ashwin Srinivasan 001 (ILP, 2008)

Qualitative System Identification from Imperfect Data. - George Macleod Coghill; Ashwin Srinivasan 001; Ross D. King (J. Artif. Intell. Res., 2008)

Incremental Identification of Qualitative Models of Biological Systems using Inductive Logic Programming. - Ashwin Srinivasan 001; Ross D. King (J. Mach. Learn. Res., 2008)

Parallel ILP for distributed-memory architectures. - Nuno A. Fonseca; Ashwin Srinivasan 001; Fernando M. A. Silva; Rui Camacho (Mach. Learn., 2009)

An investigation into feature construction to assist word sense disambiguation. - Lucia Specia; Ashwin Srinivasan 001; Sachindra Joshi; Ganesh Ramakrishnan; Maria das Graças Volpe Nunes (Mach. Learn., 2009)

BET : An Inductive Logic Programming Workbench. - Srihari Kalgi; Chirag Gosar; Prasad Gawde; Ganesh Ramakrishnan; Kekin Gada; Chander Iyer; T. V. S. Kiran; Ashwin Srinivasan 001 (ILP, 2010)

Prediction of novel precursor miRNAs using a context-sensitive hidden Markov model (CSHMM). - Sumeet Agarwal; Candida Vaz; Alok Bhattacharya; Ashwin Srinivasan 001 (BMC Bioinform., 2010)

Knowledge-Guided Identification of Petri Net Models of Large Biological Systems. - Ashwin Srinivasan 001; Michael Bain 001 (ILP, 2011)

Parameter Screening and Optimisation for ILP using Designed Experiments. - Ashwin Srinivasan 001; Ganesh Ramakrishnan (J. Mach. Learn. Res., 2011)

Topic Models with Relational Features for Drug Design. - Tanveer A. Faruquie; Ashwin Srinivasan 001; Ross D. King (ILP, 2012)

What Kinds of Relational Features Are Useful for Statistical Learning? - Amrita Saha; Ashwin Srinivasan 001; Ganesh Ramakrishnan (ILP, 2012)

ILP turns 20 - Biography and future challenges. - Stephen H. Muggleton; Luc De Raedt; David Poole 001; Ivan Bratko; Peter A. Flach; Katsumi Inoue; Ashwin Srinivasan 001 (Mach. Learn., 2012)

Data and task parallelism in ILP using MapReduce. - Ashwin Srinivasan 001; Tanveer A. Faruquie; Sachindra Joshi (Mach. Learn., 2012)

Exploratory Data Analysis Using Alternating Covers of Rules and Exceptions. - Sarmimala Saikia; Gautam Shroff; Puneet Agarwal; Ashwin Srinivasan 001; Aditeya Pandey; Gaurangi Anand (COMAD, 2014)

Interactively Visualizing Summaries of Rules and Exceptions. - Geetika Sharma; Gautam Shroff; Aditeya Pandey; Puneet Agarwal; Ashwin Srinivasan 001 (EuroVA@EuroVis, 2014)

Consensus-Based Modelling using Distributed Feature Construction. - Haimonti Dutta; Ashwin Srinivasan 001 (CoRR, 2014)

Succinctly summarizing machine usage via multi-subspace clustering of multi-sensor data. - Sarmimala Saikia; Gautam Shroff; Puneet Agarwal; Ashwin Srinivasan 001 (DSAA, 2015)

Identification of Transition Models of Biological Systems in the Presence of Transition Noise. - Ashwin Srinivasan 001; Michael Bain 001; Deepika Vatsa; Sumeet Agarwal (ILP, 2015)

Learning transition models of biological regulatory and signaling networks from noisy data. - Deepika Vatsa; Sumeet Agarwal; Ashwin Srinivasan 001 (CODS, 2016)

Generation of Near-Optimal Solutions Using ILP-Guided Sampling. - Ashwin Srinivasan 001; Gautam Shroff; Lovekesh Vig; Sarmimala Saikia (ILP, 2016)

Neuro-Symbolic EDA-Based Optimization Using ILP-Enhanced DBNs. - Sarmimala Saikia; Lovekesh Vig; Ashwin Srinivasan 001; Gautam Shroff; Puneet Agarwal; Richa Rawat (CoCo@NIPS, 2016)

Neuro-symbolic EDA-based Optimisation using ILP-enhanced DBNs. - Sarmimala Saikia; Lovekesh Vig; Ashwin Srinivasan 001; Gautam Shroff; Puneet Agarwal; Richa Rawat (CoRR, 2016)

Generation of Near-Optimal Solutions Using ILP-Guided Sampling. - Ashwin Srinivasan 001; Gautam Shroff; Lovekesh Vig; Sarmimala Saikia; Puneet Agarwal (CoRR, 2016)

ILP-assisted de novo drug design. - Rama Kaalia; Ashwin Srinivasan 001; Amit Kumar 009; Indira Ghosh (Mach. Learn., 2016)

Hybrid BiLSTM-Siamese network for FAQ Assistance. - Prerna Khurana; Puneet Agarwal; Gautam Shroff; Lovekesh Vig; Ashwin Srinivasan 001 (CIKM, 2017)

An Investigation into the Role of Domain-Knowledge on the Use of Embeddings. - Lovekesh Vig; Ashwin Srinivasan 001; Michael Bain 001; Ankit Verma (ILP, 2017)

An empirical study of on-line models for relational data streams. - Ashwin Srinivasan 001; Michael Bain 001 (Mach. Learn., 2017)

Deep Reader: Information Extraction from Document Images via Relation Extraction and Natural Language. - Vishwanath D; Rohit Rahul; Gunjan Sehgal; Swati; Arindam Chowdhury; Monika Sharma; Lovekesh Vig; Gautam Shroff; Ashwin Srinivasan 001 (ACCV Workshops, 2018)

Evolutionary RL for Container Loading. - Sarmimala Saikia; Richa Verma; Puneet Agarwal; Gautam Shroff; Lovekesh Vig; Ashwin Srinivasan 001 (ESANN, 2018)

Large-Scale Assessment of Deep Relational Machines. - Tirtharaj Dash; Ashwin Srinivasan 001; Lovekesh Vig; Oghenejokpeme I. Orhobor; Ross D. King (ILP, 2018)

Identification of biological transition systems using meta-interpreted logic programs. - Michael Bain 001; Ashwin Srinivasan 001 (Mach. Learn., 2018)

Consensus-based modeling using distributed feature construction with ILP. - Haimonti Dutta; Ashwin Srinivasan 001 (Mach. Learn., 2018)

A Reinforcement Learning Framework for Container Selection and Ship Load Sequencing in Ports. - Richa Verma; Sarmimala Saikia; Harshad Khadilkar; Puneet Agarwal; Gautam Shroff; Ashwin Srinivasan 001 (AAMAS, 2019)

Discrete Stochastic Search and Its Application to Feature-Selection for Deep Relational Machines. - Tirtharaj Dash; Ashwin Srinivasan 001; Ramprasad S. Joshi; A. Baskar (ICANN (2), 2019)

One-shot Information Extraction from Document Images using Neuro-Deductive Program Synthesis. - Vishal Sunder; Ashwin Srinivasan 001; Lovekesh Vig; Gautam Shroff; Rohit Rahul (NeSy@IJCAI, 2019)

Logical Explanations for Deep Relational Machines Using Relevance Information. - Ashwin Srinivasan 001; Lovekesh Vig; Michael Bain 001 (J. Mach. Learn. Res., 2019)

MP3vec: A Reusable Machine-Constructed Feature Representation for Protein Sequences. - Sanket Rajan Gupte; Dharm Skandh Jain; Ashwin Srinivasan 001; Raviprasad Aduri (BIBM, 2020)

Information Extraction from Document Images via FCA based Template Detection and Knowledge Graph Rule Induction. - Mouli Rastogi; Syed Afshan Ali; Mrinal Rawat; Lovekesh Vig; Puneet Agarwal; Gautam Shroff; Ashwin Srinivasan 001 (CVPR Workshops, 2020)

An Empirical Study of Iterative Knowledge Distillation for Neural Network Compression. - Sharan Yalburgi; Tirtharaj Dash; Ramya Hebbalaguppe; Srinidhi Hegde; Ashwin Srinivasan 001 (ESANN, 2020)

A Case Study of Transfer of Lesion-Knowledge. - Soundarya Krishnan; Rishab Khincha; Lovekesh Vig; Tirtharaj Dash; Ashwin Srinivasan 001 (iMIMIC/MIL3ID/LABELS@MICCAI, 2020)

CovidDiagnosis: Deep Diagnosis of COVID-19 Patients Using Chest X-Rays. - Kushagra Mahajan; Monika Sharma; Lovekesh Vig; Rishab Khincha; Soundarya Krishnan; Adithya Niranjan; Tirtharaj Dash; Ashwin Srinivasan 001; Gautam Shroff (TIA@MICCAI, 2020)

Constructing and Evaluating an Explainable Model for COVID-19 Diagnosis from Chest X-rays. - Rishab Khincha; Soundarya Krishnan; Krishnan Guru-Murthy; Tirtharaj Dash; Lovekesh Vig; Ashwin Srinivasan 001 (CoRR, 2020)

Constructing generative logical models for optimisation problems using domain knowledge. - Ashwin Srinivasan 001; Lovekesh Vig; Gautam Shroff (Mach. Learn., 2020)

Empirical Study of Data-Free Iterative Knowledge Distillation. - Het Shah; Ashwin Vaswani; Tirtharaj Dash; Ramya Hebbalaguppe; Ashwin Srinivasan 001 (ICANN (3), 2021)

Using Domain-Knowledge to Assist Lead Discovery in Early-Stage Drug Design. - Tirtharaj Dash; Ashwin Srinivasan 001; Lovekesh Vig; Arijit Roy (ILP, 2021)

Incorporating Domain Knowledge into Deep Neural Networks. - Tirtharaj Dash; Sharad Chitlangia; Aditya Ahuja; Ashwin Srinivasan 001 (CoRR, 2021)

How to Tell Deep Neural Networks What We Know. - Tirtharaj Dash; Sharad Chitlangia; Aditya Ahuja; Ashwin Srinivasan 001 (CoRR, 2021)

Using Program Synthesis and Inductive Logic Programming to solve Bongard Problems. - Atharv Sonwane; Sharad Chitlangia; Tirtharaj Dash; Lovekesh Vig; Gautam Shroff; Ashwin Srinivasan 001 (CoRR, 2021)

Solving Visual Analogies Using Neural Algorithmic Reasoning. - Atharv Sonwane; Gautam Shroff; Lovekesh Vig; Ashwin Srinivasan 001; Tirtharaj Dash (CoRR, 2021)

Incorporating symbolic domain knowledge into graph neural networks. - Tirtharaj Dash; Ashwin Srinivasan 001; Lovekesh Vig (Mach. Learn., 2021)

Solving Visual Analogies Using Neural Algorithmic Reasoning (Student Abstract). - Atharv Sonwane; Gautam Shroff; Lovekesh Vig; Ashwin Srinivasan 001; Tirtharaj Dash (AAAI, 2022)

A Program-Synthesis Challenge for ARC-Like Tasks. - Aditya Challa; Ashwin Srinivasan 001; Michael Bain 001; Gautam Shroff (ILP, 2022)

Knowledge-based Analogical Reasoning in Neuro-symbolic Latent Spaces. - Vishwa Shah; Aditya Sharma; Gautam Shroff; Lovekesh Vig; Tirtharaj Dash; Ashwin Srinivasan 001 (NeSy, 2022)

One-way Explainability Isn't The Message. - Ashwin Srinivasan 001; Michael Bain 001; Enrico W. Coiera (CoRR, 2022)

Neural Feature-Adaptation for Symbolic Predictions Using Pre-Training and Semantic Loss. - Vedant Shah; Aditya Agrawal; Lovekesh Vig; Ashwin Srinivasan 001; Gautam Shroff; Tanmay T. Verlekar (CoRR, 2022)

Inclusion of domain-knowledge into GNNs using mode-directed inverse entailment. - Tirtharaj Dash; Ashwin Srinivasan 001; A. Baskar (Mach. Learn., 2022)

Learning explanations for biological feedback with delays using an event calculus. - Ashwin Srinivasan 001; Michael Bain 001; A. Baskar (Mach. Learn., 2022)

Domain-Specific Pre-training Improves Confidence in Whole Slide Image Classification. - Soham Rohit Chitnis; Sidong Liu; Tirtharaj Dash; Tanmay Tulsidas Verlekar; Antonio Di Ieva; Shlomo Berkovsky; Lovekesh Vig; Ashwin Srinivasan 001 (EMBC, 2023)

IKD+: Reliable Low Complexity Deep Models for Retinopathy Classification. - Shreyas Bhat Brahmavar; Rohit Rajesh; Tirtharaj Dash; Lovekesh Vig; Tanmay Tulsidas Verlekar; Md Mahmudul Hasan; Tariq Mahmood Khan; Erik Meijering; Ashwin Srinivasan 001 (ICIP, 2023)

Can LLMs solve generative visual analogies? - Shrey Pandit; Gautam Shroff; Ashwin Srinivasan 001; Lovekesh Vig (IARML@IJCAI, 2023)

A Protocol for Intelligible Interaction Between Agents That Learn and Explain. - Ashwin Srinivasan 001; Michael Bain 001; A. Baskar; Enrico W. Coiera (CoRR, 2023)

Neuro-symbolic Meta Reinforcement Learning for Trading. - S. I. Harini; Gautam Shroff; Ashwin Srinivasan 001; Prayushi Faldu; Lovekesh Vig (CoRR, 2023)

Domain-Specific Pretraining Improves Confidence in Whole Slide Image Classification. - Soham Rohit Chitnis; Sidong Liu; Tirtharaj Dash; Tanmay Tulsidas Verlekar; Antonio Di Ieva; Shlomo Berkovsky; Lovekesh Vig; Ashwin Srinivasan 001 (CoRR, 2023)

Generating Novel Leads for Drug Discovery Using LLMs with Logical Feedback. - Shreyas Bhat Brahmavar; Ashwin Srinivasan 001; Tirtharaj Dash; Sowmya Ramaswamy Krishnan; Lovekesh Vig; Arijit Roy; Raviprasad Aduri (AAAI, 2024)

Composition of relational features with an application to explaining black-box predictors. - Ashwin Srinivasan 001; A. Baskar; Tirtharaj Dash; Devanshu Shah (Mach. Learn., 2024)

Accelerating Medical Image Analysis on Edge Devices: A Study with MobileOne Architecture. - Dev Gala; Jinam Keniya; Harsha Varun Marisetty; Manik Gupta; Tanmay Tulsidas Verlekar; Erik Meijering; Ashwin Srinivasan 001 (PerCom Workshops, 2025)

A model for intelligible interaction between agents that predict and explain. - A. Baskar; Ashwin Srinivasan 001; Michael Bain 001; Enrico W. Coiera (Mach. Learn., 2025)