Ashwin Srinivasan

130 papers A* 7A 2B 32C 1Misc 1Journal 65Unranked 21
YearRankTypeTitle / Venue / Authors
2026 J jnl
Routing End User Queries to Enterprise Databases.
CoRR
Saikrishna Sudarshan, Tanay Kulkarni, Manasi Patwardhan, Lovekesh Vig, Ashwin Srinivasan, Tanmay Tulsidas Verlekar
2025 J jnl
A model for intelligible interaction between agents that predict and explain.
Mach. Learn.
A. Baskar, Ashwin Srinivasan, Michael Bain, Enrico W. Coiera
2025 — conf
Accelerating Medical Image Analysis on Edge Devices: A Study with MobileOne Architecture.
PerCom Workshops
Dev Gala, Jinam Keniya, Harsha Varun Marisetty, Manik Gupta, Tanmay Tulsidas Verlekar, Erik Meijering, Ashwin Srinivasan
2025 J jnl
Symbolic Neural Generation with Applications to Lead Discovery in Drug Design.
CoRR
Ashwin Srinivasan, A. Baskar, Tirtharaj Dash, Michael Bain, Sanjay Kumar Dey, Mainak Banerjee
2024 J jnl
Composition of relational features with an application to explaining black-box predictors.
Mach. Learn.
Ashwin Srinivasan, A. Baskar, Tirtharaj Dash, Devanshu Shah
2024 A* conf
Generating Novel Leads for Drug Discovery Using LLMs with Logical Feedback.
AAAI
Shreyas Bhat Brahmavar, Ashwin Srinivasan, Tirtharaj Dash, Sowmya Ramaswamy Krishnan, Lovekesh Vig, Arijit Roy, Raviprasad Aduri
2023 J jnl
A Protocol for Intelligible Interaction Between Agents That Learn and Explain.
CoRR
Ashwin Srinivasan, Michael Bain, A. Baskar, Enrico W. Coiera
2023 — conf
Can LLMs solve generative visual analogies?
IARML@IJCAI
Shrey Pandit, Gautam Shroff, Ashwin Srinivasan, Lovekesh Vig
2023 — conf
Domain-Specific Pre-training Improves Confidence in Whole Slide Image Classification.
EMBC
Soham Rohit Chitnis, Sidong Liu, Tirtharaj Dash, Tanmay Tulsidas Verlekar, Antonio Di Ieva, Shlomo Berkovsky, Lovekesh Vig, Ashwin Srinivasan
2023 J jnl
Domain-Specific Pretraining Improves Confidence in Whole Slide Image Classification.
CoRR
Soham Rohit Chitnis, Sidong Liu, Tirtharaj Dash, Tanmay Tulsidas Verlekar, Antonio Di Ieva, Shlomo Berkovsky, Lovekesh Vig, Ashwin Srinivasan
2023 J jnl
IKD+: Reliable Low Complexity Deep Models For Retinopathy Classification.
CoRR
Shreyas Bhat Brahmavar, Rohit Rajesh, Tirtharaj Dash, Lovekesh Vig, Tanmay Tulsidas Verlekar, Md Mahmudul Hasan, Tariq Mahmood Khan, Erik Meijering, Ashwin Srinivasan
2023 B conf
IKD+: Reliable Low Complexity Deep Models for Retinopathy Classification.
ICIP
Shreyas Bhat Brahmavar, Rohit Rajesh, Tirtharaj Dash, Lovekesh Vig, Tanmay Tulsidas Verlekar, Md Mahmudul Hasan, Tariq Mahmood Khan, Erik Meijering, Ashwin Srinivasan
2023 J jnl
Neuro-symbolic Meta Reinforcement Learning for Trading.
CoRR
S. I. Harini, Gautam Shroff, Ashwin Srinivasan, Prayushi Faldu, Lovekesh Vig
2022 B conf
A Program-Synthesis Challenge for ARC-Like Tasks.
ILP
Aditya Challa, Ashwin Srinivasan, Michael Bain, Gautam Shroff
2022 J jnl
Composition of Relational Features with an Application to Explaining Black-Box Predictors.
CoRR
Ashwin Srinivasan, A. Baskar, Tirtharaj Dash, Devanshu Shah
2022 J jnl
Inclusion of domain-knowledge into GNNs using mode-directed inverse entailment.
Mach. Learn.
Tirtharaj Dash, Ashwin Srinivasan, A. Baskar
2022 C conf
Knowledge-based Analogical Reasoning in Neuro-symbolic Latent Spaces.
NeSy
Vishwa Shah, Aditya Sharma, Gautam Shroff, Lovekesh Vig, Tirtharaj Dash, Ashwin Srinivasan
2022 J jnl
Knowledge-based Analogical Reasoning in Neuro-symbolic Latent Spaces.
CoRR
Vishwa Shah, Aditya Sharma, Gautam Shroff, Lovekesh Vig, Tirtharaj Dash, Ashwin Srinivasan
2022 J jnl
Learning explanations for biological feedback with delays using an event calculus.
Mach. Learn.
Ashwin Srinivasan, Michael Bain, A. Baskar
2022 J jnl
Neural Feature-Adaptation for Symbolic Predictions Using Pre-Training and Semantic Loss.
CoRR
Vedant Shah, Aditya Agrawal, Lovekesh Vig, Ashwin Srinivasan, Gautam Shroff, Tanmay T. Verlekar
2022 J jnl
One-way Explainability Isn't The Message.
CoRR
Ashwin Srinivasan, Michael Bain, Enrico W. Coiera
2022 A* conf
Solving Visual Analogies Using Neural Algorithmic Reasoning (Student Abstract).
AAAI
Atharv Sonwane, Gautam Shroff, Lovekesh Vig, Ashwin Srinivasan, Tirtharaj Dash
2021 — conf
Empirical Study of Data-Free Iterative Knowledge Distillation.
ICANN (3)
Het Shah, Ashwin Vaswani, Tirtharaj Dash, Ramya Hebbalaguppe, Ashwin Srinivasan
2021 J jnl
How to Tell Deep Neural Networks What We Know.
CoRR
Tirtharaj Dash, Sharad Chitlangia, Aditya Ahuja, Ashwin Srinivasan
2021 J jnl
Inclusion of Domain-Knowledge into GNNs using Mode-Directed Inverse Entailment.
CoRR
Tirtharaj Dash, Ashwin Srinivasan, A. Baskar
2021 J jnl
Incorporating Domain Knowledge into Deep Neural Networks.
CoRR
Tirtharaj Dash, Sharad Chitlangia, Aditya Ahuja, Ashwin Srinivasan
2021 J jnl
Incorporating symbolic domain knowledge into graph neural networks.
Mach. Learn.
Tirtharaj Dash, Ashwin Srinivasan, Lovekesh Vig
2021 J jnl
Solving Visual Analogies Using Neural Algorithmic Reasoning.
CoRR
Atharv Sonwane, Gautam Shroff, Lovekesh Vig, Ashwin Srinivasan, Tirtharaj Dash
2021 B conf
Using Domain-Knowledge to Assist Lead Discovery in Early-Stage Drug Design.
ILP
Tirtharaj Dash, Ashwin Srinivasan, Lovekesh Vig, Arijit Roy
2021 J jnl
Using Program Synthesis and Inductive Logic Programming to solve Bongard Problems.
CoRR
Atharv Sonwane, Sharad Chitlangia, Tirtharaj Dash, Lovekesh Vig, Gautam Shroff, Ashwin Srinivasan
2020 — conf
A Case Study of Transfer of Lesion-Knowledge.
iMIMIC/MIL3ID/LABELS@MICCAI
Soundarya Krishnan, Rishab Khincha, Lovekesh Vig, Tirtharaj Dash, Ashwin Srinivasan
2020 B conf
An Empirical Study of Iterative Knowledge Distillation for Neural Network Compression.
ESANN
Sharan Yalburgi, Tirtharaj Dash, Ramya Hebbalaguppe, Srinidhi Hegde, Ashwin Srinivasan
2020 J jnl
Constructing and Evaluating an Explainable Model for COVID-19 Diagnosis from Chest X-rays.
CoRR
Rishab Khincha, Soundarya Krishnan, Krishnan Guru-Murthy, Tirtharaj Dash, Lovekesh Vig, Ashwin Srinivasan
2020 J jnl
Constructing generative logical models for optimisation problems using domain knowledge.
Mach. Learn.
Ashwin Srinivasan, Lovekesh Vig, Gautam Shroff
2020 — conf
CovidDiagnosis: Deep Diagnosis of COVID-19 Patients Using Chest X-Rays.
TIA@MICCAI
Kushagra Mahajan, Monika Sharma, Lovekesh Vig, Rishab Khincha, Soundarya Krishnan, Adithya Niranjan, Tirtharaj Dash, Ashwin Srinivasan, Gautam Shroff
2020 J jnl
Incorporating Symbolic Domain Knowledge into Graph Neural Networks.
CoRR
Tirtharaj Dash, Ashwin Srinivasan, Lovekesh Vig
2020 — conf
Information Extraction from Document Images via FCA based Template Detection and Knowledge Graph Rule Induction.
CVPR Workshops
Mouli Rastogi, Syed Afshan Ali, Mrinal Rawat, Lovekesh Vig, Puneet Agarwal, Gautam Shroff, Ashwin Srinivasan
2020 — conf
MP3vec: A Reusable Machine-Constructed Feature Representation for Protein Sequences.
BIBM
Sanket Rajan Gupte, Dharm Skandh Jain, Ashwin Srinivasan, Raviprasad Aduri
2019 A conf
A Reinforcement Learning Framework for Container Selection and Ship Load Sequencing in Ports.
AAMAS
Richa Verma, Sarmimala Saikia, Harshad Khadilkar, Puneet Agarwal, Gautam Shroff, Ashwin Srinivasan
2019 — conf
Discrete Stochastic Search and Its Application to Feature-Selection for Deep Relational Machines.
ICANN (2)
Tirtharaj Dash, Ashwin Srinivasan, Ramprasad S. Joshi, A. Baskar
2019 J jnl
Logical Explanations for Deep Relational Machines Using Relevance Information.
J. Mach. Learn. Res.
Ashwin Srinivasan, Lovekesh Vig, Michael Bain
2019 — conf
One-shot Information Extraction from Document Images using Neuro-Deductive Program Synthesis.
NeSy@IJCAI
Vishal Sunder, Ashwin Srinivasan, Lovekesh Vig, Gautam Shroff, Rohit Rahul
2019 J jnl
One-shot Information Extraction from Document Images using Neuro-Deductive Program Synthesis.
CoRR
Vishal Sunder, Ashwin Srinivasan, Lovekesh Vig, Gautam Shroff, Rohit Rahul
2018 J jnl
Consensus-based modeling using distributed feature construction with ILP.
Mach. Learn.
Haimonti Dutta, Ashwin Srinivasan
2018 — conf
Deep Reader: Information Extraction from Document Images via Relation Extraction and Natural Language.
ACCV Workshops
Vishwanath D, Rohit Rahul, Gunjan Sehgal, Swati, Arindam Chowdhury, Monika Sharma, Lovekesh Vig, Gautam Shroff, Ashwin Srinivasan
2018 J jnl
Deep Reader: Information extraction from Document images via relation extraction and Natural Language.
CoRR
Vishwanath D, Rohit Rahul, Gunjan Sehgal, Swati, Arindam Chowdhury, Monika Sharma, Lovekesh Vig, Gautam Shroff, Ashwin Srinivasan
2018 B conf
Evolutionary RL for Container Loading.
ESANN
Sarmimala Saikia, Richa Verma, Puneet Agarwal, Gautam Shroff, Lovekesh Vig, Ashwin Srinivasan
2018 J jnl
Evolutionary RL for Container Loading.
CoRR
Sarmimala Saikia, Richa Verma, Puneet Agarwal, Gautam Shroff, Lovekesh Vig, Ashwin Srinivasan
2018 J jnl
Identification of biological transition systems using meta-interpreted logic programs.
Mach. Learn.
Michael Bain, Ashwin Srinivasan
2018 B conf
Large-Scale Assessment of Deep Relational Machines.
ILP
Tirtharaj Dash, Ashwin Srinivasan, Lovekesh Vig, Oghenejokpeme I. Orhobor, Ross D. King
2018 J jnl
Logical Explanations for Deep Relational Machines Using Relevance Information.
CoRR
Ashwin Srinivasan, Lovekesh Vig, Michael Bain
2017 B conf
An Investigation into the Role of Domain-Knowledge on the Use of Embeddings.
ILP
Lovekesh Vig, Ashwin Srinivasan, Michael Bain, Ankit Verma
2017 J jnl
An empirical study of on-line models for relational data streams.
Mach. Learn.
Ashwin Srinivasan, Michael Bain
2017 A conf
Hybrid BiLSTM-Siamese network for FAQ Assistance.
CIKM
Prerna Khurana, Puneet Agarwal, Gautam Shroff, Lovekesh Vig, Ashwin Srinivasan
2016 B conf
Generation of Near-Optimal Solutions Using ILP-Guided Sampling.
ILP
Ashwin Srinivasan, Gautam Shroff, Lovekesh Vig, Sarmimala Saikia
2016 J jnl
Generation of Near-Optimal Solutions Using ILP-Guided Sampling.
CoRR
Ashwin Srinivasan, Gautam Shroff, Lovekesh Vig, Sarmimala Saikia, Puneet Agarwal
2016 J jnl
ILP-assisted de novo drug design.
Mach. Learn.
Rama Kaalia, Ashwin Srinivasan, Amit Kumar, Indira Ghosh
2016 — conf
Learning transition models of biological regulatory and signaling networks from noisy data.
CODS
Deepika Vatsa, Sumeet Agarwal, Ashwin Srinivasan
2016 — conf
Neuro-Symbolic EDA-Based Optimization Using ILP-Enhanced DBNs.
CoCo@NIPS
Sarmimala Saikia, Lovekesh Vig, Ashwin Srinivasan, Gautam Shroff, Puneet Agarwal, Richa Rawat
2016 J jnl
Neuro-symbolic EDA-based Optimisation using ILP-enhanced DBNs.
CoRR
Sarmimala Saikia, Lovekesh Vig, Ashwin Srinivasan, Gautam Shroff, Puneet Agarwal, Richa Rawat
2015 B conf
Identification of Transition Models of Biological Systems in the Presence of Transition Noise.
ILP
Ashwin Srinivasan, Michael Bain, Deepika Vatsa, Sumeet Agarwal
2015 B conf
Succinctly summarizing machine usage via multi-subspace clustering of multi-sensor data.
DSAA
Sarmimala Saikia, Gautam Shroff, Puneet Agarwal, Ashwin Srinivasan
2014 J jnl
Consensus-Based Modelling using Distributed Feature Construction.
CoRR
Haimonti Dutta, Ashwin Srinivasan
2014 Misc conf
Exploratory Data Analysis Using Alternating Covers of Rules and Exceptions.
COMAD
Sarmimala Saikia, Gautam Shroff, Puneet Agarwal, Ashwin Srinivasan, Aditeya Pandey, Gaurangi Anand
2014 — conf
Interactively Visualizing Summaries of Rules and Exceptions.
EuroVA@EuroVis
Geetika Sharma, Gautam Shroff, Aditeya Pandey, Puneet Agarwal, Ashwin Srinivasan
2012 J jnl
Data and task parallelism in ILP using MapReduce.
Mach. Learn.
Ashwin Srinivasan, Tanveer A. Faruquie, Sachindra Joshi
2012 J jnl
ILP turns 20 - Biography and future challenges.
Mach. Learn.
Stephen H. Muggleton, Luc De Raedt, David Poole, Ivan Bratko, Peter A. Flach, Katsumi Inoue, Ashwin Srinivasan
2012 B conf
Topic Models with Relational Features for Drug Design.
ILP
Tanveer A. Faruquie, Ashwin Srinivasan, Ross D. King
2012 B conf
What Kinds of Relational Features Are Useful for Statistical Learning?
ILP
Amrita Saha, Ashwin Srinivasan, Ganesh Ramakrishnan
2011 B conf
Knowledge-Guided Identification of Petri Net Models of Large Biological Systems.
ILP
Ashwin Srinivasan, Michael Bain
2011 J jnl
Parameter Screening and Optimisation for ILP using Designed Experiments.
J. Mach. Learn. Res.
Ashwin Srinivasan, Ganesh Ramakrishnan
2011 J jnl
Qualitative System Identification from Imperfect Data
CoRR
George Macleod Coghill, Ross D. King, Ashwin Srinivasan
2010 B conf
BET : An Inductive Logic Programming Workbench.
ILP
Srihari Kalgi, Chirag Gosar, Prasad Gawde, Ganesh Ramakrishnan, Kekin Gada, Chander Iyer, T. V. S. Kiran, Ashwin Srinivasan
2010 J jnl
Prediction of novel precursor miRNAs using a context-sensitive hidden Markov model (CSHMM).
BMC Bioinform.
Sumeet Agarwal, Candida Vaz, Alok Bhattacharya, Ashwin Srinivasan
2009 J jnl
An investigation into feature construction to assist word sense disambiguation.
Mach. Learn.
Lucia Specia, Ashwin Srinivasan, Sachindra Joshi, Ganesh Ramakrishnan, Maria das Graças Volpe Nunes
2009 J jnl
Parallel ILP for distributed-memory architectures.
Mach. Learn.
Nuno A. Fonseca, Ashwin Srinivasan, Fernando M. A. Silva, Rui Camacho
2009 B conf
Parameter Screening and Optimisation for ILP Using Designed Experiments.
ILP
Ashwin Srinivasan, Ganesh Ramakrishnan
2008 B conf
Feature Construction Using Theory-Guided Sampling and Randomised Search.
ILP
Sachindra Joshi, Ganesh Ramakrishnan, Ashwin Srinivasan
2008 J jnl
Incremental Identification of Qualitative Models of Biological Systems using Inductive Logic Programming.
J. Mach. Learn. Res.
Ashwin Srinivasan, Ross D. King
2008 J jnl
Qualitative System Identification from Imperfect Data.
J. Artif. Intell. Res.
George Macleod Coghill, Ashwin Srinivasan, Ross D. King
2007 — ch.
Learning Qualitative Models of Physical and Biological Systems.
Computational Discovery of Scientific Knowledge
Simon M. Garrett, George Macleod Coghill, Ashwin Srinivasan, Ross D. King
2007 — conf
USP-IBM-1 and USP-IBM-2: The ILP-based Systems for Lexical Sample WSD in SemEval-2007.
SemEval@ACL
Lucia Specia, Maria das Graças Volpe Nunes, Ashwin Srinivasan, Ganesh Ramakrishnan
2007 B conf
Using ILP to Construct Features for Information Extraction from Semi-structured Text.
ILP
Ganesh Ramakrishnan, Sachindra Joshi, Sreeram Balakrishnan, Ashwin Srinivasan
2006 J jnl
Guest editorial.
Mach. Learn.
Rui Camacho, Ross D. King, Ashwin Srinivasan
2006 B conf
ILP Through Propositionalization and Stochastic k-Term DNF Learning.
ILP
Aline Paes, Filip Zelezný, Gerson Zaverucha, C. David Page Jr., Ashwin Srinivasan
2006 J jnl
Quantitative pharmacophore models with inductive logic programming.
Mach. Learn.
Ashwin Srinivasan, David Page, Rui Camacho, Ross D. King
2006 J jnl
Randomised restarted search in ILP.
Mach. Learn.
Filip Zelezný, Ashwin Srinivasan, C. David Page Jr.
2006 B conf
Word Sense Disambiguation Using Inductive Logic Programming.
ILP
Lucia Specia, Ashwin Srinivasan, Ganesh Ramakrishnan, Maria das Graças Volpe Nunes
2005 B conf
A Study of Applying Dimensionality Reduction to Restrict the Size of a Hypothesis Space.
ILP
Ashwin Srinivasan, Ravi Kothari
2005 B conf
Five Problems in Five Areas for Five Years.
ILP
Ashwin Srinivasan
2005 A* conf
Multi-instance tree learning.
ICML
Hendrik Blockeel, David Page, Ashwin Srinivasan
2004 B conf
A Monte Carlo Study of Randomised Restarted Search in ILP.
ILP
Filip Zelezný, Ashwin Srinivasan, David Page
2004 B ed.
Inductive Logic Programming, 14th International Conference, ILP 2004, Porto, Portugal, September 6-8, 2004, Proceedings
ILP
Rui Camacho, Ross D. King, Ashwin Srinivasan
2003 J jnl
An Empirical Study of the Use of Relevance Information in Inductive Logic Programming.
J. Mach. Learn. Res.
Ashwin Srinivasan, Ross D. King, Michael Bain
2003 J jnl
ILP: A Short Look Back and a Longer Look Forward.
J. Mach. Learn. Res.
David Page, Ashwin Srinivasan
2003 J jnl
Query Transformations for Improving the Efficiency of ILP Systems.
J. Mach. Learn. Res.
Vítor Santos Costa, Ashwin Srinivasan, Rui Camacho, Hendrik Blockeel, Bart Demoen, Gerda Janssens, Jan Struyf, Henk Vandecasteele, Wim Van Laer
2003 J jnl
Statistical Evaluation of the Predictive Toxicology Challenge 2000-2001.
Bioinform.
Hannu Toivonen, Ashwin Srinivasan, Ross D. King, Stefan Kramer, Christoph Helma
2002 B conf
Lattice-Search Runtime Distributions May Be Heavy-Tailed.
ILP
Filip Zelezný, Ashwin Srinivasan, David Page
2002 B conf
The Applicability to ILP of Results Concerning the Ordering of Binomial Populations.
ILP
Ashwin Srinivasan
2001 J jnl
Are Grammatical Representations Useful for Learning from Biological Sequence Data? - A Case Study.
J. Comput. Biol.
Stephen H. Muggleton, Christopher H. Bryant, Ashwin Srinivasan, Alex Whittaker, Simon Topp, Christopher J. Rawlings
2001 J jnl
Classificatory challenge-data mining: a recipe.
Informatica (Slovenia)
Steve Moyle, Ashwin Srinivasan
2001 J jnl
Extracting Context-Sensitive Models in Inductive Logic Programming.
Mach. Learn.
Ashwin Srinivasan
2001 J jnl
The Predictive Toxicology Challenge 2000-2001.
Bioinform.
Christoph Helma, Ross D. King, Stefan Kramer, Ashwin Srinivasan
2001 J jnl
Warmr: a data mining tool for chemical data.
J. Comput. Aided Mol. Des.
Ross D. King, Ashwin Srinivasan, Luc Dehaspe
2000 B conf
A Note on Two Simple Transformations for Improving the Efficiency of an ILP System.
ILP
Vítor Santos Costa, Ashwin Srinivasan, Rui Camacho
2000 A* conf
Discovering the Structure of Partial Differential Equations from Example Behaviour.
ICML
Ljupco Todorovski, Saso Dzeroski, Ashwin Srinivasan, Jonathan P. Whiteley, David Gavaghan
2000 A* conf
Learning Chomsky-like Grammars for Biological Sequence Families.
ICML
Stephen H. Muggleton, Christopher H. Bryant, Ashwin Srinivasan
2000 — conf
Measuring Performance when Positives Are Rare: Relative Advantage versus Predictive Accuracy - A Biological Case Study.
ECML
Stephen H. Muggleton, Christopher H. Bryant, Ashwin Srinivasan
1999 J jnl
A Study of Two Sampling Methods for Analyzing Large Datasets with ILP.
Data Min. Knowl. Discov.
Ashwin Srinivasan
1999 B conf
An Assessment of ILP-Assisted Models for Toxicology and the PTE-3 Experiment.
ILP
Ashwin Srinivasan, Ross D. King, Douglas W. Bristol
1999 A* conf
An assessment of submissions made to the Predictive Toxicology Evaluation Challenge.
IJCAI
Ashwin Srinivasan, Ross D. King, Douglas W. Bristol
1999 J jnl
Feature Construction with Inductive Logic Programming: A Study of Quantitative Predictions of Biological Activity Aided by Structural Attributes.
Data Min. Knowl. Discov.
Ashwin Srinivasan, Ross D. King
1999 J jnl
Numerical Reasoning with an ILP System Capable of Lazy Evaluation and Customised Search.
J. Log. Program.
Ashwin Srinivasan, Rui Camacho
1998 B conf
Application of ILP to Problems in Chemistry and Biology (Abstract).
ILP
Ashwin Srinivasan
1998 B conf
Biochemical Knowledge Discovery Using Inductive Logic Programming.
Discovery Science
Stephen H. Muggleton, Ashwin Srinivasan, Ross D. King, Michael J. E. Sternberg
1998 J jnl
Pharmacophore Discovery Using the Inductive Logic Programming System PROGOL.
Mach. Learn.
Paul W. Finn, Stephen H. Muggleton, David Page, Ashwin Srinivasan
1998 J jnl
The discovery of indicator variables for QSAR using inductive logic programming.
J. Comput. Aided Mol. Des.
Ross D. King, Ashwin Srinivasan
1997 B conf
Carcinogenesis Predictions Using ILP.
ILP
Ashwin Srinivasan, Ross D. King, Stephen H. Muggleton, Michael J. E. Sternberg
1997 — conf
The Predictive Toxicology Evaluation Challenge.
IJCAI (1)
Ashwin Srinivasan, Ross D. King, Stephen H. Muggleton, Michael J. E. Sternberg
1997 J jnl
The discovery of indicator variables for QSAR using inductive logic programming.
J. Comput. Aided Mol. Des.
Ross D. King, Ashwin Srinivasan
1996 B conf
An Initial Experiment into Stereochemistry-Based Drug Design Using Inductive Logic Programming.
Inductive Logic Programming Workshop
Stephen H. Muggleton, David Page, Ashwin Srinivasan
1996 B conf
Feature Construction with Inductive Logic Programming: A Study of Quantitative Predictions of Biological Activity by Structural Attributes.
Inductive Logic Programming Workshop
Ashwin Srinivasan, Ross D. King
1996 J jnl
Theories for Mutagenicity: A Study in First-Order and Feature-Based Induction.
Artif. Intell.
Ashwin Srinivasan, Stephen H. Muggleton, Michael J. E. Sternberg, Ross D. King
1995 — conf
Drug Design by Machine Learning.
Machine Intelligence 15
Michael J. E. Sternberg, Ross D. King, Ashwin Srinivasan, Stephen H. Muggleton
1995 J jnl
Relating Chemical Activity to Structure: An Examination of ILP Successes.
New Gener. Comput.
Ross D. King, Michael J. E. Sternberg, Ashwin Srinivasan
1993 A* conf
Generating Explicit Orderings for Non-monotonic Logics.
AAAI
James Cussens, Anthony Hunter, Ashwin Srinivasan
1993 — conf
Inductive Logic Programming With Large-Scale Unstructured Data.
Machine Intelligence 14
Michael Bain, Ashwin Srinivasan
1992 — conf
Compression, Significance, and Accuracy.
ML
Stephen H. Muggleton, Ashwin Srinivasan, Michael Bain
1992 J jnl
Ripple down rules: Turning knowledge acquisition into knowledge maintenance.
Artif. Intell. Medicine
Paul Compton, Glenn Edwards, Byeong Kang, Leslie Lazarus, Ron Malor, Phillip Preston, Ashwin Srinivasan
1992 — conf
The Justification of Logical Theories based on Data Compression.
Machine Intelligence 13
Ashwin Srinivasan, Stephen H. Muggleton, Michael Bain