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Sastry, PS and Unnikrishnan, KP (2010) Conditional Probability-Based Significance Tests for Sequential Patterns in Multineuronal Spike Trains. In: Neural Computation, 22 (4). pp. 1025-1059.
Diekman, Casey O and Sastry, PS and Unnikrishnan, KP (2009) Statistical significance of sequential firing patterns in multi-neuronal spike trains. In: Journal of Neuroscience Methods, 182 (2). pp. 279-284.
Patnaik, Debprakash and Sastry, PS and Unnikrishnan, KP (2008) Application of frequent episode discovery for analyzing multi-neuron spike train data. In: Presented at COSYNE 2008, Computational and Systems Neuroscience Meeting, Salt Lake City, USA, Feb. 2008.
Patnaik, D and Sastry, PS and Unnikrishnan, KP (2008) Application of frequent episode discovery for analyzing multi-neuronal spike train data. In: Computational and Systems Neuroscience Meeting, Salt Lake City, USA, (COSYNE2008).
Patnaik, D and Sastry, PS and Unnikrishnan, KP (2008) Datamining Schemes for discovering functional connectivity patterns for multi-neuronal spike trains. In: 4th Int Workshop on Statistical Analysis of Neural Data (SAND-4), Pittsburgh, USA.
Patnaik, Debprakash and Sastry, PS and Unnikrishnan, KP (2008) Inferring neuronal network connectivity from spike data: A temporal data mining approach. In: Scientific Programming, 16 (1). pp. 49-77.
Diekman, C and Sastry, PS and Unnikrishnan, KP (2008) Using Correlation counts to infer relative strengths of functional connections in multi-neuronal spike trains. In: 4th Int Workshop on Statistical Analysis of Neural Data (SAND-4), Pittsburgh, USA.
Sastry, PS and Unnikrishnan, KP (2008) A novel statistical significance test for inferring relative strengths of functional connectivity patterns from multi-neuronal spike trains. In: 4th Int Workshop on Statistical Analysis of Neural Data (SAND-4), Pittsburgh, USA.
Laxman, Srivatsan and Sastry, PS and Unnikrishnan, KP (2007) Discovering Frequent Generalized Episodes When Events Persist for Different Durations. In: IEEE Transactions on Knowledge and Data Engineering, 19 (9). pp. 1188-1201.
Unnikrishnan, KP and Shadid, Basel Q and Sastry, PS and Laxman, Srivatsan (2007) Root cause diagnostics using temporal data mining. Patent Number(s) US 7509234. Patent Assignee(s) GM Global Technology Operations, Inc..
Laxman, Srivatsan and Sastry, PS and Unnikrishnan, KP (2007) A fast algorithm for finding frequent episodes in event streams. In: KDD '07 Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining, Aug. 2007, New York, NY.
Unnikrishnan, KP and Ramakrishnan, Naren and Sastry, PS and Uthurusamy, Ramasamy (2006) Network Reconstruction from dynamic data. In: SIGKDD Explorations, 8 (2). pp. 90-91.
Srivatsan, Laxman and Sastry, PS and Unnikrishnan, KP (2005) Discovering Frequent Episodes and Learning Hidden Markov Models: A Formal Connection. In: IEEE Transactions on Knowledge and Data Engineering, 17 (11). pp. 1505-17.
Laxman, Srivatsan and Sastry, PS and Unnikrishnan, KP (2004) Fast algorithms for frequent episode discovery in event sequences. In: Proc. Third Int. Workshop on Mining Temporal and Sequential Data, August 2004, Sigkdd, Seattle, WA.
Sastry, PS and Magesh, M and Unnikrishnan, KP (2002) Two timescale analysis of the Alopex algorithm for optimization. In: Neural Computation, 14 (11). pp. 2729-2750.
Laxman, Srivatsan and Sastry, PS and Unnikrishnan, KP (2002) Generalized frequent episodes in Event Sequences. In: Presented at Workshop on Temporal Data Mining, July 2002, Edmonton, Canada.
Sastry, PS and Shah, Shesha and Singh, S and Unnikrishnan, KP (1999) Role of feedback in mammalian vision: a new hypothesis and a computational model. In: Vision Research, 39 (1). pp. 131-148.
Shah, Shesha and Sastry, PS and Unnikrishnan, KP (1998) A Feedback Based Algorithm for Line Detection. In: Indian Conference on Vision, Graphics and Image Processing (ICVGIP), Dec. 1998, New Delhi.
Sastry, PS and Santharam, G and Unnikrishnan, KP (1994) Memory Neuron Networks for Identification and Control of Dynamical Systems. In: IEEE Transactions on Neural Networks, 5 (2). pp. 306-319.
