Mahesan Niranjan

170 papers A* 2A 4B 6C 4Misc 18Journal 89Unranked 45

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	3D audio-visual indoor scene reconstruction and semantics completion for virtual reality from a single $360^{\circ }$ RGB-D image. Virtual Real. Mona Alawadh, Atiyeh Alinaghi, Mahesan Niranjan, Hansung Kim
2025	J	`jnl`	A variational autoencoder for probabilistic non-negative matrix factorisation. Pattern Anal. Appl. Steven Squires, Adam Prügel-Bennett, Mahesan Niranjan
2025	J	`jnl`	Arch-LLM: Taming LLMs for Neural Architecture Generation via Unsupervised Discrete Representation Learning. CoRR Deshani Geethika Poddenige, Sachith Seneviratne, Damith A. Senanayake, Mahesan Niranjan, Ponnuthurai N. Suganthan, Saman K. Halgamuge
2025	J	`jnl`	Automated Data Enrichment using Confidence-Aware Fine-Grained Debate among Open-Source LLMs for Mental Health and Online Safety. CoRR Junyu Mao, Anthony Hills, Talia Tseriotou, Maria Liakata, Aya Shamir, Dan Sayda, Dana Atzil-Slonim, Natalie Djohari, Arpan Mandal, Silke Roth, Pamela Ugwudike, Mahesan Niranjan, Stuart E. Middleton
2025	J	`jnl`	Balancing misclassification errors in image-based inference using problem domain semantics and a nested cascade architecture. Neural Comput. Appl. Xin Du, Rajesh Jena, Katayoun Farrahi, Mahesan Niranjan
2025	—	`conf`	How does the Machine Perceive Depth for Indoor Single Images with CNN? CVPR Workshops Yihong Wu, Yuwen Heng, Mahesan Niranjan, Hansung Kim
2024	B	`conf`	3D Semantic Scene Completion From A Depth Map With Unsupervised Learning For Semantics Prioritisation. ICIP Mona Alawadh, Mahesan Niranjan, Hansung Kim
2024	J	`jnl`	Discrepancy-based Diffusion Models for Lesion Detection in Brain MRI. CoRR Keqiang Fan, Xiaohao Cai, Mahesan Niranjan
2024	J	`jnl`	Discrepancy-based diffusion models for lesion detection in brain MRI. Comput. Biol. Medicine Keqiang Fan, Xiaohao Cai, Mahesan Niranjan
2024	—	`conf`	Do Prompt Positions Really Matter? NAACL-HLT (Findings) Junyu Mao, Stuart E. Middleton, Mahesan Niranjan
2024	J	`jnl`	EpiCURB: Learning to Derive Epidemic Control Policies. IEEE Pervasive Comput. Andrei C. Rusu, Katayoun Farrahi, Mahesan Niranjan
2024	J	`jnl`	Non-negative Subspace Feature Representation for Few-shot Learning in Medical Imaging. CoRR Keqiang Fan, Xiaohao Cai, Mahesan Niranjan
2024	J	`jnl`	Non-negative subspace feature representation for few-shot learning in medical imaging. Image Vis. Comput. Keqiang Fan, Xiaohao Cai, Mahesan Niranjan
2024	J	`jnl`	Protein language models meet reduced amino acid alphabets. Bioinform. Ioan Ieremie, Rob M. Ewing, Mahesan Niranjan
2024	J	`jnl`	Semantic Scene Completion with Multi-Feature Data Balancing Network. CoRR Mona Alawadh, Mahesan Niranjan, Hansung Kim
2024	—	`conf`	SliceFormer: Deep Dense Depth Estimation from a Single Indoor Omnidirectional Image Using a Slice-Based Transformer. ICEIC Yihong Wu, Yuwen Heng, Mahesan Niranjan, Hansung Kim
2023	J	`jnl`	Causal Analysis of Physiological Sleep Data Using Granger Causality and Score-Based Structure Learning. Sensors Alex Thomas, Mahesan Niranjan, Julian Legg
2023	Misc	`conf`	Depth Estimation for a Single Omnidirectional Image with Reversed-Gradient Warming-up Thresholds Discriminator. ICASSP Yihong Wu, Yuwen Heng, Mahesan Niranjan, Hansung Kim
2023	J	`jnl`	Depth Insight - Contribution of Different Features to Indoor Single-image Depth Estimation. CoRR Yihong Wu, Yuwen Heng, Mahesan Niranjan, Hansung Kim
2023	J	`jnl`	Few-shot Learning for Inference in Medical Imaging with Subspace Feature Representations. CoRR Jiahui Liu, Keqiang Fan, Xiaohao Cai, Mahesan Niranjan
2023	J	`jnl`	GO-LDA: Generalised Optimal Linear Discriminant Analysis. CoRR Jiahui Liu, Xiaohao Cai, Mahesan Niranjan
2023	—	`conf`	IIHT: Medical Report Generation with Image-to-Indicator Hierarchical Transformer. ICONIP (6) Keqiang Fan, Xiaohao Cai, Mahesan Niranjan
2023	J	`jnl`	IIHT: Medical Report Generation with Image-to-Indicator Hierarchical Transformer. CoRR Keqiang Fan, Xiaohao Cai, Mahesan Niranjan
2023	J	`jnl`	Prompt position really matters in few-shot and zero-shot NLU tasks. CoRR Junyu Mao, Stuart E. Middleton, Mahesan Niranjan
2023	J	`jnl`	Quantum annealing-based clustering of single cell RNA-seq data. Briefings Bioinform. Michal Kubacki, Mahesan Niranjan
2023	J	`jnl`	Thinking Outside the Box: Orthogonal Approach to Equalizing Protected Attributes. CoRR Jiahui Liu, Xiaohao Cai, Mahesan Niranjan
2022	J	`jnl`	Convex Multi-View Clustering Via Robust Low Rank Approximation With Application to Multi-Omic Data. IEEE ACM Trans. Comput. Biol. Bioinform. Omar Shetta, Mahesan Niranjan, Srinandan Dasmahapatra
2022	—	`conf`	Deep Cascade Learning for Optimal Medical Image Feature Representation. MLHC Junwen Wang, Xin Du, Katayoun Farrahi, Mahesan Niranjan
2022	—	`conf`	Flattening the Curve Through Reinforcement Learning Driven Test and Trace Policies. PervasiveHealth Andrei C. Rusu, Katayoun Farrahi, Mahesan Niranjan
2022	B	`conf`	Robust 3D rotation invariant local binary pattern for volumetric texture classification. ICPR Shengyu Lu, Sasan Mahmoodi, Mahesan Niranjan
2022	J	`jnl`	Robustness under parameter and problem domain alterations of Bayesian optimization methods for chemical reactions. J. Cheminformatics Rubaiyat Mohammad Khondaker, Stephen Gow, Samantha Kanza, Jeremy G. Frey, Mahesan Niranjan
2022	—	`conf`	Room Acoustic Properties Estimation from a Single 360° Photo. EUSIPCO Mona Alawadh, Yihong Wu, Yuwen Heng, Luca Remaggi, Mahesan Niranjan, Hansung Kim
2022	J	`jnl`	TransformerGO: predicting protein-protein interactions by modelling the attention between sets of gene ontology terms. Bioinform. Ioan Ieremie, Rob M. Ewing, Mahesan Niranjan
2021	—	`conf`	Automated gastrointestinal abnormalities detection from endoscopic images. ICIIS Premananth Gowtham, Mahesan Niranjan, Kaneswaran Anantharajah
2021	—	`conf`	Depth Estimation from a Single Omnidirectional Image using Domain Adaptation. CVMP Yihong Wu, Yuwen Heng, Mahesan Niranjan, Hansung Kim
2021	J	`jnl`	Information Bottleneck Theory Based Exploration of Cascade Learning. Entropy Xin Du, Katayoun Farrahi, Mahesan Niranjan
2021	J	`jnl`	The AI for Scientific Discovery Network Patterns Samantha Kanza, Colin Leonard Bird, Mahesan Niranjan, William McNeill, Jeremy Graham Frey
2020	J	`jnl`	A Numerical Measure of the Instability of Mapper-Type Algorithms. J. Mach. Learn. Res. Francisco Belchí Guillamón, Jacek Brodzki, Matthew Burfitt, Mahesan Niranjan
2020	J	`jnl`	Construction of Minimum Spanning Trees from Financial Returns using Rank Correlation. CoRR Tristan Millington, Mahesan Niranjan
2020	J	`jnl`	Estimation of Gaussian mixture models via tensor moments with application to online learning. Pattern Recognit. Lett. Donya Rahmani, Mahesan Niranjan, Damien Fay, Akiko Takeda, Jacek Brodzki
2020	J	`jnl`	Long short-term memory networks and laglasso for bond yield forecasting: Peeping inside the black box. CoRR Manuel Nunes, Enrico H. Gerding, Frank McGroarty, Mahesan Niranjan
2020	J	`jnl`	Partial correlation financial networks. Appl. Netw. Sci. Tristan Millington, Mahesan Niranjan
2020	J	`jnl`	Understanding and Enhancing Mixed Sample Data Augmentation. CoRR Ethan Harris, Antonia Marcu, Matthew Painter, Mahesan Niranjan, Adam Prügel-Bennett, Jonathon S. Hare
2019	J	`jnl`	A Biologically Inspired Visual Working Memory for Deep Networks. CoRR Ethan Harris, Mahesan Niranjan, Jonathon S. Hare
2019	J	`jnl`	A Variational Autoencoder for Probabilistic Non-Negative Matrix Factorisation. CoRR Steven Squires, Adam Prügel-Bennett, Mahesan Niranjan
2019	J	`jnl`	A comparison of multitask and single task learning with artificial neural networks for yield curve forecasting. Expert Syst. Appl. Manuel Nunes, Enrico H. Gerding, Frank McGroarty, Mahesan Niranjan
2019	J	`jnl`	A numerical measure of the instability of Mapper-type algorithms. CoRR Francisco Belchí Guillamón, Jacek Brodzki, Matthew Burfitt, Mahesan Niranjan
2019	B	`conf`	Classification and Regression Analysis of Lung Tumors from Multi-level Gene Expression Data. IJCNN Pratheeba Jeyananthan, Mahesan Niranjan
2019	J	`jnl`	Minimum description length as an objective function for non-negative matrix factorization. CoRR Steven Squires, Adam Prügel-Bennett, Mahesan Niranjan
2019	—	`conf`	On Comparing the Influences of Exogenous Information on Bitcoin Prices and Stock Index Values. MARBLE Luis Montesdeoca, Mahesan Niranjan
2019	C	`conf`	Quantifying Influence in Financial Markets via Partial Correlation Network Inference. ISPA Tristan Millington, Mahesan Niranjan
2019	B	`conf`	Representation-dimensionality Trade-off in Biological Sequence-based Inference. IJCNN Bahman Asadi, Mahesan Niranjan
2019	Misc	`conf`	Saliency Map on Cnns for Protein Secondary Structure Prediction. ICASSP Guillermo Romero Moreno, Mahesan Niranjan, Adam Prügel-Bennett
2019	Misc	`conf`	Transfer learning across human activities using a cascade neural network architecture. UbiComp Xin Du, Katayoun Farrahi, Mahesan Niranjan
2019	J	`jnl`	Uncovering extensive post-translation regulation during human cell cycle progression by integrative multi-'omics analysis. BMC Bioinform. Gregory M. Parkes, Mahesan Niranjan
2019	C	`conf`	Variational Autoencoder for Non-Negative Matrix Factorization with Exogenous Inputs Applied to Financial Data Modelling. ISPA Luis Montesdeoca, Steven Squires, Mahesan Niranjan
2018	J	`jnl`	Deep Cascade Learning. IEEE Trans. Neural Networks Learn. Syst. Enrique S. Marquez, Jonathon S. Hare, Mahesan Niranjan
2018	J	`jnl`	Improved understanding of aqueous solubility modeling through topological data analysis. J. Cheminformatics Mariam Pirashvili, Lee Steinberg, Francisco Belchí Guillamón, Mahesan Niranjan, Jeremy G. Frey, Jacek Brodzki
2017	—	`conf`	A Method of Integrating Spatial Proteomics and Protein-Protein Interaction Network Data. ICONIP (5) Steven Squires, Rob M. Ewing, Adam Prügel-Bennett, Mahesan Niranjan
2017	—	`conf`	Non-Negative Matrix Factorization with Exogenous Inputs for Modeling Financial Data. ICONIP (2) Steven Squires, Luis Montesdeoca, Adam Prügel-Bennett, Mahesan Niranjan
2017	J	`jnl`	Rank Selection in Nonnegative Matrix Factorization using Minimum Description Length. Neural Comput. Steven Squires, Adam Prügel-Bennett, Mahesan Niranjan
2017	—	`conf`	Robust Portfolio Risk Minimization Using the Graphical Lasso. ICONIP (2) Tristan Millington, Mahesan Niranjan
2016	—	`conf`	Extending the feature set of a data-driven artificial neural network model of pricing financial options. SSCI Luis Montesdeoca, Mahesan Niranjan
2016	J	`jnl`	Rotation invariant texture descriptors based on Gaussian Markov random fields for classification. Pattern Recognit. Lett. Chathurika Dharmagunawardhana, Sasan Mahmoodi, Michael J. Bennett, Mahesan Niranjan
2015	J	`jnl`	Defining the Gold Standard Definitions for the Morphology of Sinhala Words. Res. Comput. Sci. Viraj Welgama, Ruvan Weerasinghe, Mahesan Niranjan
2015	J	`jnl`	Detection of social events in streams of social multimedia. Int. J. Multim. Inf. Retr. Jonathon S. Hare, Sina Samangooei, Mahesan Niranjan, Nicholas Gibbins
2015	B	`conf`	MIAT: A novel attribute selection approach to better predict upper gastrointestinal cancer. DSAA Avi Rosenfeld, David G. Graham, Rifat A. Hamoudi, Rommel Butawan, Victor Eneh, Saif Khan, Haroon Miah, Mahesan Niranjan, Laurence B. Lovat
2015	J	`jnl`	Outlier detection at the transcriptome-proteome interface. Bioinform. Yawwani Gunawardana, Shuhei Fujiwara, Akiko Takeda, Jeongmin Woo, Christopher H. Woelk, Mahesan Niranjan
2015	J	`jnl`	Scalable Reordering Models for SMT based on Multiclass SVM. Prague Bull. Math. Linguistics Abdullah Alrajeh, Mahesan Niranjan
2015	J	`jnl`	Single-cell transcriptional analysis to uncover regulatory circuits driving cell fate decisions in early mouse development. Bioinform. Haifen Chen, Jing Guo, Shital K. Mishra, Paul Robson, Mahesan Niranjan, Jie Zheng
2015	J	`jnl`	Speaker Adaptation Applied to Sinhala Speech Recognition. Int. J. Comput. Linguistics Appl. Thilini Nadungodage, Ruvan Weerasinghe, Mahesan Niranjan
2015	—	`conf`	Statistical Machine Translation from and into Morphologically Rich and Low Resourced Languages. CICLing (1) Randil Pushpananda, Ruvan Weerasinghe, Mahesan Niranjan
2014	C	`conf`	An Inhomogeneous Bayesian Texture Model for Spatially Varying Parameter Estimation. ICPRAM Chathurika Dharmagunawardhana, Sasan Mahmoodi, Michael J. Bennett, Mahesan Niranjan
2014	—	`conf`	Bayesian Reordering Model with Feature Selection. WMT@ACL Abdullah Alrajeh, Mahesan Niranjan
2014	J	`jnl`	Biomedical visual data analysis to build an intelligent diagnostic decision support system in medical genetics. Artif. Intell. Medicine Kaya Kuru, Mahesan Niranjan, Yusuf Tunca, Erhan Osvank, Tayyaba Azim
2014	—	`conf`	Computational Models of Object Recognition - Goal, Role and Success. VISAPP (1) Tayyaba Azim, Mahesan Niranjan
2014	J	`jnl`	Gaussian Markov random field based improved texture descriptor for image segmentation. Image Vis. Comput. Chathurika Dharmagunawardhana, Sasan Mahmoodi, Michael J. Bennett, Mahesan Niranjan
2014	A*	`conf`	Large-scale Reordering Model for Statistical Machine Translation using Dual Multinomial Logistic Regression. EMNLP Abdullah Alrajeh, Mahesan Niranjan
2014	C	`conf`	Memory-efficient large-scale linear support vector machine. ICMV Abdullah Alrajeh, Akiko Takeda, Mahesan Niranjan
2014	—	`conf`	Quantitative Analysis of Pulmonary Emphysema using Isotropic Gaussian Markov Random Fields. VISAPP (3) Chathurika Dharmagunawardhana, Sasan Mahmoodi, Michael J. Bennett, Mahesan Niranjan
2014	Misc	`conf`	Sinhala-Tamil Machine Translation: Towards better Translation Quality. ALTA Randil Pushpananda, Ruvan Weerasinghe, Mahesan Niranjan
2014	—	`conf`	Texture Classification with Fisher Kernel Extracted from the Continuous Models of RBM. VISAPP (2) Tayyaba Azim, Mahesan Niranjan
2013	J	`jnl`	Bridging the gap between transcriptome and proteome measurements identifies post-translationally regulated genes. Bioinform. Yawwani Gunawardana, Mahesan Niranjan
2013	—	`conf`	Compact codebook design for visual scene recognition by Sequential Input Space Carving. MLSP B. Mayurathan, U. A. J. Pinidiyaarachchi, Mahesan Niranjan
2013	J	`jnl`	Design of a Low-Power On-Body ECG Classifier for Remote Cardiovascular Monitoring Systems. IEEE J. Emerg. Sel. Topics Circuits Syst. Taihai Chen, Evangelos B. Mazomenos, Koushik Maharatna, Srinandan Dasmahapatra, Mahesan Niranjan
2013	A*	`conf`	Enriching Texture Analysis with Semantic Data. CVPR Tim Matthews, Mark S. Nixon, Mahesan Niranjan
2013	—	`conf`	Inducing discrimination in biologically inspired models of visual scene recognition. MLSP Tayyaba Azim, Mahesan Niranjan
2013	—	`conf`	Inferring Time-Delayed Gene Regulatory Networks Using Cross-Correlation and Sparse Regression. ISBRA Piyushkumar A. Mundra, Jie Zheng, Mahesan Niranjan, Roy E. Welsch, Jagath C. Rajapakse
2013	J	`jnl`	On Acoustic Emotion Recognition: Compensating for Covariate Shift. IEEE Trans. Speech Audio Process. Ali Hassan, Robert I. Damper, Mahesan Niranjan
2013	J	`jnl`	Simultaneous pursuit of out-of-sample performance and sparsity in index tracking portfolios. Comput. Manag. Sci. Akiko Takeda, Mahesan Niranjan, Jun-ya Gotoh, Yoshinobu Kawahara
2013	—	`conf`	Social Event Detection Via Sparse Multi-modal Feature Selection and Incremental Density Based Clustering. MediaEval Sina Samangooei, Jonathon S. Hare, David Dupplaw, Mahesan Niranjan, Nicholas Gibbins, Paul H. Lewis, Jamie Davies, Neha Jain, John Preston
2012	J	`jnl`	A Review of Codebook Models in Patch-Based Visual Object Recognition. J. Signal Process. Syst. Amirthalingam Ramanan, Mahesan Niranjan
2012	—	`conf`	Establishment of a Diagnostic Decision Support System in Genetic Dysmorphology. ICMLA (2) Kaya Kuru, Mahesan Niranjan, Yusuf Tunca
2012	J	`jnl`	Gaussian process modelling for Bioinform. Wei Liu, Mahesan Niranjan
2012	J	`jnl`	Markov Chain Monte Carlo Methods for State-Space Models with Point Process Observations. Neural Comput. Ke Yuan, Mark A. Girolami, Mahesan Niranjan
2012	—	`conf`	On the Trade-Off of Accuracy and Computational Complexity for Classifying Normal and Abnormal ECG in Remote CVD Monitoring Systems. SiPS Taihai Chen, Evangelos B. Mazomenos, Koushik Maharatna, Srinandan Dasmahapatra, Mahesan Niranjan
2012	J	`jnl`	State and parameter estimation of the heat shock response system using Kalman and particle filters. Bioinform. Xin Liu, Mahesan Niranjan
2012	A	`conf`	Unsupervised Texture Segmentation using Active Contours and Local Distributions of Gaussian Markov Random Field Parameters. BMVC Chathurika Dharmagunawardhana, Sasan Mahmoodi, Michael J. Bennett, Mahesan Niranjan
2011	J	`jnl`	Exploitation of Machine Learning Techniques in Modelling Phrase Movements for Machine Translation. J. Mach. Learn. Res. Yizhao Ni, Craig Saunders, Sándor Szedmák, Mahesan Niranjan
2011	J	`jnl`	Online Variational Inference for State-Space Models with Point-Process Observations. Neural Comput. Andrew Zammit-Mangion, Ke Yuan, Visakan Kadirkamanathan, Mahesan Niranjan, Guido Sanguinetti
2010	J	`jnl`	Approximate low-rank factorization with structured factors. Comput. Stat. Data Anal. Ivan Markovsky, Mahesan Niranjan
2010	J	`jnl`	Asymptotic mean and variance of Gini correlation for bivariate normal samples. IEEE Trans. Signal Process. Weichao Xu, Y. S. Hung, Mahesan Niranjan, Minfen Shen
2010	J	`jnl`	Estimating a State-Space Model from Point Process Observations: A Note on Convergence. Neural Comput. Ke Yuan, Mahesan Niranjan
2010	—	`conf`	Exploiting Long-Range Dependencies in Protein PRIB Yizhao Ni, Mahesan Niranjan
2010	J	`jnl`	Inference from Low Precision Transcriptome Data Representation. J. Signal Process. Syst. Salih Tuna, Mahesan Niranjan
2010	J	`jnl`	Reducing the algorithmic variability in transcriptome-based inference. Bioinform. Salih Tuna, Mahesan Niranjan
2010	J	`jnl`	The application of structured learning in natural language processing. Mach. Transl. Yizhao Ni, Craig Saunders, Sándor Szedmák, Mahesan Niranjan
2009	—	`conf`	Cross-Platform Analysis with Binarized Gene Expression Data. PRIB Salih Tuna, Mahesan Niranjan
2009	—	`conf`	Handling phrase reorderings for machine translation. ACL/IJCNLP (2) Yizhao Ni, Craig Saunders, Sándor Szedmák, Mahesan Niranjan
2009	Misc	`conf`	Modelling uncertainty in transcriptome measurements enhances network component analysis of yeast metabolic cycle. ICASSP C. Q. Chang, Y. S. Hung, Mahesan Niranjan
2009	—	`ed.`	Pattern Recognition in Bioinformatics, 4th IAPR International Conference, PRIB 2009, Sheffield, UK, September 7-9, 2009. Proceedings PRIB Visakan Kadirkamanathan, Guido Sanguinetti, Mark A. Girolami, Mahesan Niranjan, Josselin Noirel
2009	J	`jnl`	Remote Homology Detection Using a Kernel Method that Combines Sequence and Secondary-Structure Similarity Scores. Silico Biol. Daniela Wieser, Mahesan Niranjan
2009	—	`conf`	Sequential Hierarchical Pattern Clustering. PRIB Bassam Farran, Amirthalingam Ramanan, Mahesan Niranjan
2008	B	`conf`	Applying Cost-Sensitive Multiobjective Genetic Programming to Feature Extraction for Spam E-mail Filtering. EuroGP Yang Zhang, Hongyu Li, Mahesan Niranjan, Peter I. Rockett
2008	J	`jnl`	Enhancing Automatic Construction of Gene Subnetworks by Integrating Multiple Sources of Information. J. Signal Process. Syst. Sujimarn Suwannaroj, Mahesan Niranjan
2008	J	`jnl`	Mining Protein Database using Machine Learning Techniques. J. Integr. Bioinform. Renata da Silva Camargo, Mahesan Niranjan
2007	J	`jnl`	Prediction of Gene Expression in Embryonic Structures of PLoS Comput. Biol. Anastasia Samsonova, Mahesan Niranjan, Steven Russell, Alvis Brazma
2006	—	`conf`	Automatic Face Recognition Using Stereo Images. ICASSP (5) Anjali Bharatkumar Samani, Joab R. Winkler, Mahesan Niranjan
2006	—	`conf`	Outlier Detection in Benchmark Classification Tasks. ICASSP (5) Hongyu Li, Mahesan Niranjan
2005	—	`ed.`	Deterministic and Statistical Methods in Machine Learning, First International Workshop, Sheffield, UK, September 7-10, 2004, Revised Lectures Deterministic and Statistical Methods in Machine Learning Joab R. Winkler, Mahesan Niranjan, Neil D. Lawrence
2004	J	`jnl`	Reducing the variability in cDNA microarray image processing by Bayesian inference. Bioinform. Neil D. Lawrence, Marta Milo, Mahesan Niranjan, Penny Rashbass, Stephan Soullier
2003	—	`conf`	Bayesian processing of microarray images. NNSP Neil D. Lawrence, Marta Milo, Mahesan Niranjan, Penny Rashbass, Stephan Soullier
2003	J	`jnl`	Sequential Bayesian Decoding with a Population of Neurons. Neural Comput. Si Wu, Danmei Chen, Mahesan Niranjan, Shun-ichi Amari
2003	—	`conf`	Subspaces of text discrimination with application to biological literature. NNSP Mahesan Suwannaroj, Mahesan Niranjan
2002	J	`jnl`	Diphone subspace mixture trajectory models for HMM complementation. Speech Commun. Klaus Reinhard, Mahesan Niranjan
2001	A	`conf`	Extractive summarization of voicemail using lexical and prosodic feature subset selection. INTERSPEECH Konstantinos Koumpis, Steve Renals, Mahesan Niranjan
2001	J	`jnl`	Speech enhancement using a Bayesian evidence approach. Comput. Speech Lang. Gaafar M. K. Saleh, Mahesan Niranjan
2000	A	`conf`	Data-dependent kernels in svm classification of speech patterns. INTERSPEECH Nathan Smith, Mahesan Niranjan
2000	J	`jnl`	Dynamic Learning with the EM Algorithm for Neural Networks. J. VLSI Signal Process. João F. G. de Freitas, Mahesan Niranjan, Andrew H. Gee
2000	J	`jnl`	Hierarchical Bayesian Models for Regularization in Sequential Learning. Neural Comput. João F. G. de Freitas, Mahesan Niranjan, Andrew H. Gee
2000	Misc	`conf`	Matched filter design for diphone subspace models. ICASSP Klaus Reinhard, Mahesan Niranjan
2000	J	`jnl`	Neuro-computing versus linear statistical techniques applied to liver transplant monitoring: a comparative study. IEEE Trans. Biomed. Eng. David G. Melvin, Mahesan Niranjan, Richard W. Prager, Andrew K. Trull, Vikki F. Hughes
2000	J	`jnl`	Sequential Monte Carlo Methods to Train Neural Network Models. Neural Comput. João F. G. de Freitas, Mahesan Niranjan, Andrew H. Gee, Arnaud Doucet
1999	Misc	`conf`	Diphone multi-trajectory subspace models. ICASSP Klaus Reinhard, Mahesan Niranjan
1999	—	`conf`	Diphone subspace models for phone-based HMM complementation. EUROSPEECH Klaus Reinhard, Mahesan Niranjan
1999	Misc	`conf`	Hybrid sequential Monte Carlo/Kalman methods to train neural networks in non-stationary environments. ICASSP João F. G. de Freitas, Mahesan Niranjan, Andrew H. Gee
1999	J	`jnl`	Parametric subspace modeling of speech transitions. Speech Commun. Klaus Reinhard, Mahesan Niranjan
1999	Misc	`conf`	Sequential Bayesian computation of logistic regression models. ICASSP Mahesan Niranjan
1999	—	`conf`	Speech Modelling Using Subspace and EM Techniques. NIPS Gavin Smith, João F. G. de Freitas, Tony Robinson, Mahesan Niranjan
1998	J	`jnl`	Feature selection using expected attainable discrimination. Pattern Recognit. Lett. David R. Lovell, Christopher R. Dance, Mahesan Niranjan, Richard W. Prager, Kevin J. Dalton, R. Derom
1998	—	`conf`	Global Optimisation of Neural Network Models via Sequential Sampling. NIPS João F. G. de Freitas, Mahesan Niranjan, Arnaud Doucet, Andrew H. Gee
1998	—	`conf`	Global optimisation of neural network models via sequential sampling-importance resampling. ICSLP João F. G. de Freitas, Sue E. Johnson, Mahesan Niranjan, Andrew H. Gee
1998	Misc	`conf`	Markov chain Monte Carlo methods for speech enhancement. ICASSP Jaco Vermaak, Mahesan Niranjan
1998	Misc	`conf`	Parametric subspace modelling of speech transitions. ICASSP Klaus Reinhard, Mahesan Niranjan
1998	A	`conf`	Realisable Classifiers: Improving Operating Performance on Variable Cost Problems. BMVC Martin J. J. Scott, Mahesan Niranjan, Richard W. Prager
1998	Misc	`conf`	Speech enhancement in a Bayesian framework. ICASSP Gaafar M. K. Saleh, Mahesan Niranjan
1997	J	`jnl`	Average-Case Learning Curves for Radial Basis Function Networks. Neural Comput. Sean B. Holden, Mahesan Niranjan
1997	J	`jnl`	Examples in Medical Applications. IEEE Signal Process. Mag. Mahesan Niranjan
1997	—	`conf`	Regularisation in Sequential Learning Algorithms. NIPS João F. G. de Freitas, Mahesan Niranjan, Andrew H. Gee
1997	J	`jnl`	The past, present, and future of neural networks for signal processing. IEEE Signal Process. Mag. Jenq-Neng Hwang, Sun-Yuan Kung, Mahesan Niranjan, José C. Príncipe
1996	J	`jnl`	Pruning with Replacement on Limited Resource Allocating Networks by F-Projections. Neural Comput. Christophe Molina, Mahesan Niranjan
1996	—	`conf`	Sequential Tracking in Pricing Financial Options using Model Based and Neural Network Approaches. NIPS Mahesan Niranjan
1995	J	`jnl`	On the practical applicability of VC dimension bounds. Neural Comput. Sean B. Holden, Mahesan Niranjan
1995	J	`jnl`	On the statistical physics of radial basis function networks. Neural Process. Lett. Sean B. Holden, Mahesan Niranjan
1995	—	`conf`	The use of maximum a posteriori parameters in linear prediction of speech. EUROSPEECH Gaafar M. K. Saleh, Mahesan Niranjan, William J. Fitzgerald
1995	Misc	`conf`	Vocal tract modelling with recurrent neural networks. ICASSP T. L. Burrows, Mahesan Niranjan
1994	J	`jnl`	Fully vector-quantized neural network-based code-excited nonlinear predictive speech coding. IEEE Trans. Speech Audio Process. Lizhong Wu, Mahesan Niranjan, Frank Fallside
1994	—	`conf`	On the design of nonlinear speech predictors with recurrent nets. ICASSP (2) Lizhong Wu, Mahesan Niranjan
1994	—	`conf`	Recursive tracking of formants in speech signals. ICASSP (2) Mahesan Niranjan, Ingemar J. Cox, Sunita L. Hingorani
1993	J	`jnl`	A Function Estimation Approach to Sequential Learning with Neural Networks. Neural Comput. Visakan Kadirkamanathan, Mahesan Niranjan
1992	Misc	`conf`	Models of dynamic complexity for time-series prediction (neural networks). ICASSP Visakan Kadirkamanathan, Mahesan Niranjan, Frank Fallside
1991	Misc	`conf`	A nonlinear model for time series prediction and signal interpolation. ICASSP Mahesan Niranjan, Visakan Kadirkamanathan
1991	Misc	`conf`	Nonlinear adaptive filtering in nonstationary environments. ICASSP Visakan Kadirkamanathan, Mahesan Niranjan
1990	J	`jnl`	A theoretical investigation into the performance of the Hopfield model. IEEE Trans. Neural Networks Sreeram V. B. Aiyer, Mahesan Niranjan, Frank Fallside
1990	Misc	`conf`	CELP coding with adaptive output-error model identification. ICASSP Mahesan Niranjan
1990	—	`conf`	Sequential Adaptation of Radial Basis Function Networks. NIPS Visakan Kadirkamanathan, Mahesan Niranjan, Frank Fallside
1990	—	`conf`	Speech Feature Extraction Using Neural Networks. EURASIP Workshop Mahesan Niranjan, Frank Fallside
1989	Misc	`conf`	Temporal decomposition: a framework for enhanced speech recognition. ICASSP Mahesan Niranjan, Frank Fallside
1988	J	`jnl`	Book reviews. Artif. Intell. Rev. Tony Dodd, Leonard Bolc, Paul Taylor, Judith Wusterman, Blay Whitby, Carlton McDonald, J. Garwood, Jim Sholicar, Wendy J. Milne, Michael Pengelly, Tony Priest, Antony Galton, Mahesan Niranjan, D. Rainton, J. R. Thomas, Steve Hedges, Barbara Gorayska
1987	—	`conf`	On modelling the dynamics of speech patterns. ECST Mahesan Niranjan, Frank Fallside