Journal Publications

SarathChandar, A. P., Khapra, M., Larochelle, H., and Ravindran, B. (2016) "Correlational Neural Networks". Neural Computation, 28(2):257-285.

Moustafa, A.A., Chakravarthy, S., Phillips, J. Gupta, A., Keri, S, Polner, B., Frank, M. J., Jahanshahi, M. (2016). Motor symptoms in Parkinson's disease: A unified framework. Neuroscience &Biobehavioral Reviews, 68:727-40. doi: 10.1016/j.neubiorev.2016.07.010. Epub 2016 Jul 12.

De, A., Chakravarthy, V.S., Levin, M. (2016). A computational model of planarian regeneration. International Journal of Parallel, Emergent and Distributed Systems, 1-17; doi:10.1080/17445760.2016.1185521.

Moustafa A.A., Chakravarthy, V.S, Phillips, J.R., Crouse, J.J., Gupta, A.,, Frank, M.J., Hall, J.M., Jahanshahi, M. (2016) Interrelations between cognitive dysfunction and motor symptoms of Parkinson's disease: Behavioral and neural studies. Reviews in the Neurosciences, 27(5):535-48;doi: 10.1515/revneuro-2015-0070.

Philips R.T., Chhabria K., Chakravarthy V.S. (2016) Vascular Dynamics Aid a Coupled Neurovascular Network Learn Sparse Independent Features: A Computational Model. Frontiers in Neural Circuits. 10:7. DOI:10.3389/fncir.2016.00007.

Chhabria K., Chakravarthy V.S. (2016) Low-dimensional models of 'Neuro-glio-vascular unit' for describing neural dynamics under normal and energy-starved conditions, Frontiers in Neurology.

Balakrishnan M., ChakravarthyV.S., Guhathakurta S. (2015) "Simulation of cardiac arrhythmias using a 2D heterogeneous whole heart model", Frontiers in Physiology, 6: 00374.

BalasubramaniP. P., Chakravarthy, V. S. , Ali,M.,Ravindran,B.,Moustafa, A. A. (2015) "Identifying the basal ganglia network model markers for medication-induced impulsivity in Parkinson's Disease patients," PloS one, 10: e0127542.

Mandali, M. Rengaswamy, V. S. Chakravarthy, and A. A. Moustafa, (2015) "A spiking Basal Ganglia model of synchrony, exploration and decision making," Frontiers in Neuroscience, 9: 191.

Soman, K., Muralidharan, V., Chakravarthy, (2016) V.S., An oscillatory network model of head direction, spatially periodic cells and place cellsusing locomotor inputs, Bioarxivdoi: http://dx.doi.org/10.1101/080267

Prasanna, P., Chandar, S., Ravindran, B. (2015) "TSEB: More Efficient Thompson Sampling for Policy Learning". arXiv.preprint arXiv:1510.02874.

Rajendran J., Prasanna, P., Ravindran, B., and Khapra, M. M. (2015) "ADAAPT: A Deep Architecture for Adaptive Policy Transfer from Multiple Sources". arXiv preprint arXiv:1510.02879.

Lakshminarayanan, A. S., Sharma, S., and Ravindran, B. (2017) " Dynamic Action Repetition for Deep Reinforcement Learning". To appear in the proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17). AAAI Press.

Mandali A., Chakravarthy V.S. (2016). Probing the role of medication, DBS electrode position and antidromic activation on impulsivity using a computational model of Basal Ganglia. Frontiers in Human Neuroscience.ID:197629 (accepted).

Gala, N., Venkatramani, S., Raghunathan, A, Kamakoti,V. "Approximate Error Detection with Stochastic Checkers" IEEE Transactions on Very Large Scale Integration (submitted).

Manav Choudhary, Jaikishan Jayakumar, Balaraman Ravindran& Partha P Mitra.” Application of Deep Learning architectures for Computer Vision in automated classification of neurons within the Nissl stained neurohistological images”.

Conference proceedings

Lakshminarayanan, A. S., Sharma, S., and Ravindran, B. (2016) " Dynamic Frame skip Deep Q Network". Accepted at the IJCAI Workshop on Deep Reinforcement Learning: Frontiers and Challenges, New Yok City, July 2016.

Gangal, V., Ravindran, B., and Narayanam, R. (2016) "HEMI: Hyperedge Majority Influence Maximization". Accepted at the Second IJCAI Workshop on Social Influence Analysis (SocInf 2016), New York City, July 2016.

Krishnamurthy, R., Lakshminarayanan, A. S., Kumar, P., Ravindran, B. (2016) "Hierarchical Reinforcement Learning using Spatio-Temporal Abstractions and Deep Neural Networks". Accepted at the ICML Workshop on Abstraction in Reinforcement Learning, New York City, June 2016.

Rajendran, J., Khapra, M. M., Chandar, S., Ravindran, B. (2016) "Bridge Correlational Neural Networks for Multilingual Multimodal Representation Learning". In the Proceedings of the Fifteenth Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human LanguageTechnologies (NAACL:HLT 2016), pp. 171-181. ACL.

Nahas, P., James, F., Ravindran, B., and Shah, S. V. (2016) "RRT-HX: RRT with Heuristic Extend Operations for Motion Planning in Non-Holonomic Systems". To appear in the proceedings of the 2016 ASME IDETC/CIE Mechanisms and Robotics Conference. ASME.

Aditi Singh, Toufiq Parag, ManavChoudary, Jaikishan Jayakumar, BalaramanRavindran, Daniel Ferrante, Partha Mitra. (2016) Automated segmentation of Nissl-stained somata from whole-brain histological image data. Proceedings for society for neuroscience meeting, Novermber2016, 470.03/NNN48.

Sukhendu Das, Girraj Pahariya, VenuVangala Gopal, Jaikishan Jayakumar, Daniel D. Ferrante, Partha P. Mitra.(2016) Automated Detection of GFP Labelled Nuclei in Whole-Brain Light-Microscopic Datasets for Mouse with High Precision and Recall. Proceedings for society for neuroscience meeting,November 2016 470.03/NNN49.

Ashika Sharma, Jaikishan Jayakumar, Ankit Sharma, DiptiDeodhare, SutanuChakraborti, P Sreenivasa Kumar, and P Partha Mitra (2016) A novel method for extracting brain connectivity from Neuroscience text articles. Proceedings for society for neuroscience meeting, 2016 470.03/NNN52.

Sreerag O V, Ryan Phillips, SrinivasaChakravarthy, Mriganka Sur. (2016) A computational model of astrocyte induced modulation of synaptic plasticity and normalization. Soc. Neurosci., 2016.

Neel Gala, SwagathVenkatramani, AnandRaghunathan, V. Kamakoti, (2016) "STOCK: Stochastic Checkers for low-overhead error detection", ACM/IEEE International Symposium Low Power Electronics and Design, August 2016.

Ashika Sharma, Ankit Sharma, DiptiDeodhare, SutanuChakraborti, P Sreenivasa Kumar, and P Partha Mitra. (2016) Case Representation and Retrieval Techniques for Neuroanatomical Connectivity Extraction from PubMed. Proceedings of ICCBR,2016, pp 370-386.

Neel Gala, SwagathVenkatramani, AnandRaghunathan, V. Kamakoti, (2016) "STOCK: Stochastic Checkers for low-overhead error detection", ACM/IEEE International Symposium Low Power Electronics and Design, August 2016.

Girraj Pahariya, Venu V. Gopal, Sukhendu Das, Partha P Mitra and Daniel D. Ferrante (2016) "Analysis of Cre:H2B-GFP Labelled GABAergic Interneurons Data from the Mouse Brain Architecture Project", In Inaugural Workshop on Computational Brain Research, IIT Madras, India, January 4-8, 2016.

Saha, A., Acharya, A., Ravindran, B., and Ghosh, J. (2015) "Nonparametric Poisson Factorization Machine". In the Proceedings of the Fifteenth IEEE International Conference on Data Mining (ICDM 2015), pp. 967-972. IEEE Press.

Sankar, V., and Ravindran, B. (2015) "Parallelization of Game Theoretic Centrality Algorithms". In the Special Issue on Applications of Data Sciences of Sadhana, The Engineering Proceedings of the Indian Academy of Sciences, September 2015, Volume 40, Issue 6, pp. 1821-1843. Springer.

Saha, A., Misra, R., and Ravindran, B. (2015) "Scalable Bayesian Matrix Factorization". Accepted at the Sixth International Workshop on Mining Ubiquitous and Social Environments (MUSE), co-located with ECML/PKDD 2015, Porto, Portugal. + Garlapati, A., Raghunathan, A., Nagarajan, V., and Ravindran, B. (2015) "A Reinforcement Learning Approach to Online Learning of Decision Trees". Accepted at the European Workshop on Reinforcement Learning (EWRL 2015).

Sankar, V., Shivashankar, S., and Ravindran. B. (2015) "CEIL: A Scalable, Resolution Limit Free Approach for Detecting Communities in Large Networks". In the Proceedings of the Twenty Fourth International Joint Conference on Artificial Intelligence (IJCAI 2015), pp. 2097-2103. AAAI Press.

Satchidanand, S. N., Ananthapadmanaban, H., and Ravindran, B. (2015) "Extended Discriminative Random Walk: A Hypergraph Approach to Multi-View Multi-Relational Transductive Learning". In the Proceedings of the Twenty Fourth International Joint Conference on Artificial Intelligence (IJCAI 2015), pp. 3791-3797. AAAI Press.

Patil, S., and Ravindran, B. (2015) "Active Learning based Weak Supervision for Textual Survey Response Classification". In the Proceedings of the Sixteenth International Conference on Intelligent Text Processing and Computational Linguistics (CICLing 2015), Vol. 2, pp. 309-320. Springer.

Pasumarthi, R. K., Narayanam, R., and Ravindran, B. (2015) "Near Optimal Strategies for Targeted Marketing on Social Networks". In the Proceedings of the Fourteenth International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2015), pp. 1679-1680. ACM Press. (Short Paper)

Gurukar, S., Ranu, S., and Ravindran, B. (2015) "COMMIT : A Scalable Approach to Mining Communication Motifs from Dynamic Networks". in the Proceedings of ACM SIGMOD Conference on Management of Data, pp. 475-489. ACM Press.

Roy, S., and Ravindran, B. (2015) "Measuring Network Centrality Using Hypergraphs". In the Proceedings of the Second ACM-IKDD Conference on Data Sciences (IKDD CoDS). ACM Digital Library.

Rongali, S., SarathChandar, A. P., and Ravindran, B. (2015) "From Multiple Views to Single View : A Neural Network Approach". In the Proceedings of the Second ACM-IKDD Conference on Data Sciences (IKDD CoDS). ACM Digital Library.

Thesis

Aditi Singh (2016) Automated Cell Segmentation of Nissl Stained Mouse Brain Images. BTech/ MTech thesis in Electrical Engineering, IIT-Madras.

Sneha Reddy Aenugu (2016) Automation of quality control process in mouse brain architecture project. BTech/ MTechthesis in Electrical Engineering, IIT-Madras.