Mahesan Niranjan

ORCID

Publication Activity (10 Years)

Years Active: 1987-2024
Publications (10 Years): 52

Top Venues

Publications

Keqiang Fan, Xiaohao Cai, Mahesan Niranjan
Discrepancy-based Diffusion Models for Lesion Detection in Brain MRI. CoRR (2024)
Andrei C. Rusu, Katayoun Farrahi, Mahesan Niranjan
EpiCURB: Learning to Derive Epidemic Control Policies. IEEE Pervasive Comput. 23 (1) (2024)
Yihong Wu, Yuwen Heng, Mahesan Niranjan, Hansung Kim
SliceFormer: Deep Dense Depth Estimation from a Single Indoor Omnidirectional Image Using a Slice-Based Transformer. ICEIC (2024)
Ioan Ieremie, Rob M. Ewing, Mahesan Niranjan
Protein language models meet reduced amino acid alphabets. Bioinform. 40 (2) (2024)
Keqiang Fan, Xiaohao Cai, Mahesan Niranjan
Non-negative Subspace Feature Representation for Few-shot Learning in Medical Imaging. CoRR (2024)
Jiahui Liu, Xiaohao Cai, Mahesan Niranjan
Thinking Outside the Box: Orthogonal Approach to Equalizing Protected Attributes. CoRR (2023)
Jiahui Liu, Xiaohao Cai, Mahesan Niranjan
GO-LDA: Generalised Optimal Linear Discriminant Analysis. CoRR (2023)
Junyu Mao, Stuart E. Middleton, Mahesan Niranjan
Prompt position really matters in few-shot and zero-shot NLU tasks. CoRR (2023)
Jiahui Liu, Keqiang Fan, Xiaohao Cai, Mahesan Niranjan
Few-shot Learning for Inference in Medical Imaging with Subspace Feature Representations. CoRR (2023)
Alex Thomas, Mahesan Niranjan, Julian Legg
Causal Analysis of Physiological Sleep Data Using Granger Causality and Score-Based Structure Learning. Sensors 23 (23) (2023)
Keqiang Fan, Xiaohao Cai, Mahesan Niranjan
IIHT: Medical Report Generation with Image-to-Indicator Hierarchical Transformer. ICONIP (6) (2023)
Yihong Wu, Yuwen Heng, Mahesan Niranjan, Hansung Kim
Depth Insight - Contribution of Different Features to Indoor Single-image Depth Estimation. CoRR (2023)
Yihong Wu, Yuwen Heng, Mahesan Niranjan, Hansung Kim
Depth Estimation for a Single Omnidirectional Image with Reversed-Gradient Warming-up Thresholds Discriminator. ICASSP (2023)
Keqiang Fan, Xiaohao Cai, Mahesan Niranjan
IIHT: Medical Report Generation with Image-to-Indicator Hierarchical Transformer. CoRR (2023)
Mona Alawadh, Yihong Wu, Yuwen Heng, Luca Remaggi, Mahesan Niranjan, Hansung Kim
Room Acoustic Properties Estimation from a Single 360° Photo. EUSIPCO (2022)
Andrei C. Rusu, Katayoun Farrahi, Mahesan Niranjan
Flattening the Curve Through Reinforcement Learning Driven Test and Trace Policies. PervasiveHealth (2022)
Junwen Wang, Xin Du, Katayoun Farrahi, Mahesan Niranjan
Deep Cascade Learning for Optimal Medical Image Feature Representation. MLHC (2022)
Ioan Ieremie, Rob M. Ewing, Mahesan Niranjan
TransformerGO: predicting protein-protein interactions by modelling the attention between sets of gene ontology terms. Bioinform. 38 (8) (2022)
Shengyu Lu, Sasan Mahmoodi, Mahesan Niranjan
Robust 3D rotation invariant local binary pattern for volumetric texture classification. ICPR (2022)
Omar Shetta, Mahesan Niranjan, Srinandan Dasmahapatra
Convex Multi-View Clustering Via Robust Low Rank Approximation With Application to Multi-Omic Data. IEEE ACM Trans. Comput. Biol. Bioinform. 19 (6) (2022)
Rubaiyat Mohammad Khondaker, Stephen Gow, Samantha Kanza, Jeremy G. Frey, Mahesan Niranjan
Robustness under parameter and problem domain alterations of Bayesian optimization methods for chemical reactions. J. Cheminformatics 14 (1) (2022)
Samantha Kanza, Colin Leonard Bird, Mahesan Niranjan, William McNeill, Jeremy Graham Frey
. Patterns 2 (1) (2021)
Xin Du, Katayoun Farrahi, Mahesan Niranjan
Information Bottleneck Theory Based Exploration of Cascade Learning. Entropy 23 (10) (2021)
Premananth Gowtham, Mahesan Niranjan, Kaneswaran Anantharajah
Automated gastrointestinal abnormalities detection from endoscopic images. ICIIS (2021)
Yihong Wu, Yuwen Heng, Mahesan Niranjan, Hansung Kim
Depth Estimation from a Single Omnidirectional Image using Domain Adaptation. CVMP (2021)
Tristan Millington, Mahesan Niranjan
Construction of Minimum Spanning Trees from Financial Returns using Rank Correlation. CoRR (2020)
Donya Rahmani, Mahesan Niranjan, Damien Fay, Akiko Takeda, Jacek Brodzki
Estimation of Gaussian mixture models via tensor moments with application to online learning. Pattern Recognit. Lett. 131 (2020)
Francisco Belchí Guillamón, Jacek Brodzki, Matthew Burfitt, Mahesan Niranjan
A Numerical Measure of the Instability of Mapper-Type Algorithms. J. Mach. Learn. Res. 21 (2020)
Tristan Millington, Mahesan Niranjan
Partial correlation financial networks. Appl. Netw. Sci. 5 (1) (2020)
Ethan Harris, Antonia Marcu, Matthew Painter, Mahesan Niranjan, Adam Prügel-Bennett, Jonathon S. Hare
Understanding and Enhancing Mixed Sample Data Augmentation. CoRR (2020)
Manuel Nunes, Enrico Gerding, Frank McGroarty, Mahesan Niranjan
Long short-term memory networks and laglasso for bond yield forecasting: Peeping inside the black box. CoRR (2020)
Ethan Harris, Mahesan Niranjan, Jonathon S. Hare
A Biologically Inspired Visual Working Memory for Deep Networks. CoRR (2019)
Tristan Millington, Mahesan Niranjan
Quantifying Influence in Financial Markets via Partial Correlation Network Inference. ISPA (2019)
Pratheeba Jeyananthan, Mahesan Niranjan
Classification and Regression Analysis of Lung Tumors from Multi-level Gene Expression Data. IJCNN (2019)
Steven Squires, Adam Prügel-Bennett, Mahesan Niranjan
A Variational Autoencoder for Probabilistic Non-Negative Matrix Factorisation. CoRR (2019)
Luis Montesdeoca, Steven Squires, Mahesan Niranjan
Variational Autoencoder for Non-Negative Matrix Factorization with Exogenous Inputs Applied to Financial Data Modelling. ISPA (2019)
Luis Montesdeoca, Mahesan Niranjan
On Comparing the Influences of Exogenous Information on Bitcoin Prices and Stock Index Values. MARBLE (2019)
Gregory M. Parkes, Mahesan Niranjan
Uncovering extensive post-translation regulation during human cell cycle progression by integrative multi-'omics analysis. BMC Bioinform. 20 (1) (2019)
Steven Squires, Adam Prügel-Bennett, Mahesan Niranjan
Minimum description length as an objective function for non-negative matrix factorization. CoRR (2019)
Manuel Nunes, Enrico Gerding, Frank McGroarty, Mahesan Niranjan
A comparison of multitask and single task learning with artificial neural networks for yield curve forecasting. Expert Syst. Appl. 119 (2019)
Francisco Belchí Guillamón, Jacek Brodzki, Matthew Burfitt, Mahesan Niranjan
A numerical measure of the instability of Mapper-type algorithms. CoRR (2019)
Bahman Asadi, Mahesan Niranjan
Representation-dimensionality Trade-off in Biological Sequence-based Inference. IJCNN (2019)
Xin Du, Katayoun Farrahi, Mahesan Niranjan
Transfer learning across human activities using a cascade neural network architecture. UbiComp (2019)
Guillermo Romero Moreno, Mahesan Niranjan, Adam Prügel-Bennett
Saliency Map on Cnns for Protein Secondary Structure Prediction. ICASSP (2019)
Mariam Pirashvili, Lee Steinberg, Francisco Belchí Guillamón, Mahesan Niranjan, Jeremy G. Frey, Jacek Brodzki
Improved understanding of aqueous solubility modeling through topological data analysis. J. Cheminformatics 10 (1) (2018)
Enrique S. Marquez, Jonathon S. Hare, Mahesan Niranjan
Deep Cascade Learning. IEEE Trans. Neural Networks Learn. Syst. 29 (11) (2018)
Steven Squires, Rob Ewing, Adam Prügel-Bennett, Mahesan Niranjan
A Method of Integrating Spatial Proteomics and Protein-Protein Interaction Network Data. ICONIP (5) (2017)
Steven Squires, Luis Montesdeoca, Adam Prügel-Bennett, Mahesan Niranjan
Non-Negative Matrix Factorization with Exogenous Inputs for Modeling Financial Data. ICONIP (2) (2017)
Steven Squires, Adam Prügel-Bennett, Mahesan Niranjan
Rank Selection in Nonnegative Matrix Factorization using Minimum Description Length. Neural Comput. 29 (8) (2017)
Tristan Millington, Mahesan Niranjan
Robust Portfolio Risk Minimization Using the Graphical Lasso. ICONIP (2) (2017)
Luis Montesdeoca, Mahesan Niranjan
Extending the feature set of a data-driven artificial neural network model of pricing financial options. SSCI (2016)
Chathurika Dharmagunawardhana, Sasan Mahmoodi, Michael J. Bennett, Mahesan Niranjan
Rotation invariant texture descriptors based on Gaussian Markov random fields for classification. Pattern Recognit. Lett. 69 (2016)
Viraj Welgama, Ruvan Weerasinghe, Mahesan Niranjan
Defining the Gold Standard Definitions for the Morphology of Sinhala Words. Res. Comput. Sci. 90 (2015)
Yawwani Gunawardana, Shuhei Fujiwara, Akiko Takeda, Jeongmin Woo, Christopher H. Woelk, Mahesan Niranjan
Outlier detection at the transcriptome-proteome interface. Bioinform. 31 (15) (2015)
Haifen Chen, Jing Guo, Shital K. Mishra, Paul Robson, Mahesan Niranjan, Jie Zheng
Single-cell transcriptional analysis to uncover regulatory circuits driving cell fate decisions in early mouse development. Bioinform. 31 (7) (2015)
Avi Rosenfeld, David G. Graham, Rifat A. Hamoudi, Rommel Butawan, Victor Eneh, Saif Khan, Haroon Miah, Mahesan Niranjan, Laurence B. Lovat
MIAT: A novel attribute selection approach to better predict upper gastrointestinal cancer. DSAA (2015)
Randil Pushpananda, Ruvan Weerasinghe, Mahesan Niranjan
Statistical Machine Translation from and into Morphologically Rich and Low Resourced Languages. CICLing (1) (2015)
Jonathon S. Hare, Sina Samangooei, Mahesan Niranjan, Nicholas Gibbins
Detection of social events in streams of social multimedia. Int. J. Multim. Inf. Retr. 4 (4) (2015)
Thilini Nadungodage, Ruvan Weerasinghe, Mahesan Niranjan
Speaker Adaptation Applied to Sinhala Speech Recognition. Int. J. Comput. Linguistics Appl. 6 (1) (2015)
Abdullah Alrajeh, Mahesan Niranjan
Scalable Reordering Models for SMT based on Multiclass SVM. Prague Bull. Math. Linguistics 103 (2015)
Abdullah Alrajeh, Akiko Takeda, Mahesan Niranjan
Memory-efficient large-scale linear support vector machine. ICMV (2014)
Chathurika Dharmagunawardhana, Sasan Mahmoodi, Michael J. Bennett, Mahesan Niranjan
Quantitative Analysis of Pulmonary Emphysema using Isotropic Gaussian Markov Random Fields. VISAPP (3) (2014)
Randil Pushpananda, Ruvan Weerasinghe, Mahesan Niranjan
Sinhala-Tamil Machine Translation: Towards better Translation Quality. ALTA (2014)
Chathurika Dharmagunawardhana, Sasan Mahmoodi, Michael J. Bennett, Mahesan Niranjan
Gaussian Markov random field based improved texture descriptor for image segmentation. Image Vis. Comput. 32 (11) (2014)
Tayyaba Azim, Mahesan Niranjan
Computational Models of Object Recognition - Goal, Role and Success. VISAPP (1) (2014)
Tayyaba Azim, Mahesan Niranjan
Texture Classification with Fisher Kernel Extracted from the Continuous Models of RBM. VISAPP (2) (2014)
Chathurika Dharmagunawardhana, Sasan Mahmoodi, Michael J. Bennett, Mahesan Niranjan
An Inhomogeneous Bayesian Texture Model for Spatially Varying Parameter Estimation. ICPRAM (2014)
Abdullah Alrajeh, Mahesan Niranjan
Large-scale Reordering Model for Statistical Machine Translation using Dual Multinomial Logistic Regression. EMNLP (2014)
Abdullah Alrajeh, Mahesan Niranjan
Bayesian Reordering Model with Feature Selection. WMT@ACL (2014)
Kaya Kuru, Mahesan Niranjan, Yusuf Tunca, Erhan Osvank, Tayyaba Azim
Biomedical visual data analysis to build an intelligent diagnostic decision support system in medical genetics. Artif. Intell. Medicine 62 (2) (2014)
Yawwani Gunawardana, Mahesan Niranjan
Bridging the gap between transcriptome and proteome measurements identifies post-translationally regulated genes. Bioinform. 29 (23) (2013)
Ali Hassan, Robert I. Damper, Mahesan Niranjan
On Acoustic Emotion Recognition: Compensating for Covariate Shift. IEEE Trans. Speech Audio Process. 21 (7) (2013)
Tayyaba Azim, Mahesan Niranjan
Inducing discrimination in biologically inspired models of visual scene recognition. MLSP (2013)
Tim Matthews, Mark S. Nixon, Mahesan Niranjan
Enriching Texture Analysis with Semantic Data. CVPR (2013)
Piyushkumar A. Mundra, Jie Zheng, Mahesan Niranjan, Roy E. Welsch, Jagath C. Rajapakse
Inferring Time-Delayed Gene Regulatory Networks Using Cross-Correlation and Sparse Regression. ISBRA (2013)
Akiko Takeda, Mahesan Niranjan, Jun-ya Gotoh, Yoshinobu Kawahara
Simultaneous pursuit of out-of-sample performance and sparsity in index tracking portfolios. Comput. Manag. Sci. 10 (1) (2013)
Sina Samangooei, Jonathon S. Hare, David Dupplaw, Mahesan Niranjan, Nicholas Gibbins, Paul H. Lewis, Jamie Davies, Neha Jain, John Preston
Social Event Detection Via Sparse Multi-modal Feature Selection and Incremental Density Based Clustering. MediaEval (2013)
Taihai Chen, Evangelos B. Mazomenos, Koushik Maharatna, Srinandan Dasmahapatra, Mahesan Niranjan
Design of a Low-Power On-Body ECG Classifier for Remote Cardiovascular Monitoring Systems. IEEE J. Emerg. Sel. Topics Circuits Syst. 3 (1) (2013)
Ke Yuan, Mark A. Girolami, Mahesan Niranjan
Markov Chain Monte Carlo Methods for State-Space Models with Point Process Observations. Neural Comput. 24 (6) (2012)
Kaya Kuru, Mahesan Niranjan, Yusuf Tunca
Establishment of a Diagnostic Decision Support System in Genetic Dysmorphology. ICMLA (2) (2012)
Amirthalingam Ramanan, Mahesan Niranjan
A Review of Codebook Models in Patch-Based Visual Object Recognition. J. Signal Process. Syst. 68 (3) (2012)
Chathurika Dharmagunawardhana, Sasan Mahmoodi, Michael J. Bennett, Mahesan Niranjan
Unsupervised Texture Segmentation using Active Contours and Local Distributions of Gaussian Markov Random Field Parameters. BMVC (2012)
Wei Liu, Mahesan Niranjan
mRNA regulation in spatio-temporal Bicoid profile. Bioinform. 28 (3) (2012)
Taihai Chen, Evangelos B. Mazomenos, Koushik Maharatna, Srinandan Dasmahapatra, Mahesan Niranjan
On the Trade-Off of Accuracy and Computational Complexity for Classifying Normal and Abnormal ECG in Remote CVD Monitoring Systems. SiPS (2012)
Xin Liu, Mahesan Niranjan
State and parameter estimation of the heat shock response system using Kalman and particle filters. Bioinform. 28 (11) (2012)
Yizhao Ni, Craig Saunders, Sándor Szedmák, Mahesan Niranjan
Exploitation of Machine Learning Techniques in Modelling Phrase Movements for Machine Translation. J. Mach. Learn. Res. 12 (2011)
Andrew Zammit Mangion, Ke Yuan, Visakan Kadirkamanathan, Mahesan Niranjan, Guido Sanguinetti
Online Variational Inference for State-Space Models with Point-Process Observations. Neural Comput. 23 (8) (2011)
Weichao Xu, Y. S. Hung, Mahesan Niranjan, Minfen Shen
Asymptotic mean and variance of Gini correlation for bivariate normal samples. IEEE Trans. Signal Process. 58 (2) (2010)
Salih Tuna, Mahesan Niranjan
Reducing the algorithmic variability in transcriptome-based inference. Bioinform. 26 (9) (2010)
Ke Yuan, Mahesan Niranjan
Estimating a State-Space Model from Point Process Observations: A Note on Convergence. Neural Comput. 22 (8) (2010)
Yizhao Ni, Craig Saunders, Sándor Szedmák, Mahesan Niranjan
The application of structured learning in natural language processing. Mach. Transl. 24 (2) (2010)
Salih Tuna, Mahesan Niranjan
Inference from Low Precision Transcriptome Data Representation. J. Signal Process. Syst. 58 (3) (2010)
Ivan Markovsky, Mahesan Niranjan
Approximate low-rank factorization with structured factors. Comput. Stat. Data Anal. 54 (12) (2010)
Yizhao Ni, Mahesan Niranjan
-Sheet Secondary Structure Prediction. PRIB (2010)
Daniela Wieser, Mahesan Niranjan
Remote Homology Detection Using a Kernel Method that Combines Sequence and Secondary-Structure Similarity Scores. Silico Biol. 9 (3) (2009)
Bassam Farran, Amirthalingam Ramanan, Mahesan Niranjan
Sequential Hierarchical Pattern Clustering. PRIB (2009)
C. Q. Chang, Y. S. Hung, Mahesan Niranjan
Modelling uncertainty in transcriptome measurements enhances network component analysis of yeast metabolic cycle. ICASSP (2009)
Yizhao Ni, Craig Saunders, Sándor Szedmák, Mahesan Niranjan
Handling phrase reorderings for machine translation. ACL/IJCNLP (2) (2009)
Salih Tuna, Mahesan Niranjan
Cross-Platform Analysis with Binarized Gene Expression Data. PRIB (2009)
Yang Zhang, Hongyu Li, Mahesan Niranjan, Peter I. Rockett
Applying Cost-Sensitive Multiobjective Genetic Programming to Feature Extraction for Spam E-mail Filtering. EuroGP (2008)

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Publication Activity (10 Years)

Top Topics

Top Venues

Mahesan Niranjan