Journal papers and major conference proceedings

• Philipp H. W. Hoffmann.
  A Hitchhiker's Guide to Automatic Differentiation.
  Numerical Algorithms, 1-37, 2015. doi:10.1007/s11075-015-0067-6
• Oleksandr Manzyuk, Barak A. Pearlmutter, Alexey Andreyevich Radul, David R. Rush, and Jeffrey Mark Siskind.
  Confusion of Tagged Perturbations in Forward Automatic Differentiation of Higher-Order Functions.
  Higher Order and Symbolic Computation, To Appear. arXiv:1211.4892
• Barak A. Pearlmutter and Conor J. Houghton.
  Dreams, mnemonics, and tuning for criticality.
  Behavioral and Brain Sciences 36(6):625-26, 2013. doi:10.1017/S0140525X13001404
  Open Peer Commentary on Sue Llewellyn, Such stuff as dreams are made on? Elaborative encoding, the ancient art of memory, and the hippocampus
• Míriam R. García, Barak A. Pearlmutter, Peter E. Wellstead, and Richard H. Middleton.
  A slow axon antidromic blockade hypothesis for tremor reduction via deep brain stimulation.
  PLOS ONE 8(9):e73456, 2013. doi:10.1371/journal.pone.0073456
• Vince D. Calhoun, Vamsi K. Potluru, Ronald Phlypo, Rogers F. Silva, Barak A. Pearlmutter, Arvind Caprihan, Sergey M. Plis, and Tülay Adalı.
  Independent Component Analysis for Brain fMRI Does Indeed Select for Maximal Independence.
  PLOS ONE 8(8):e73309, 2013. doi:10.1371/journal.pone.0073309
• Vamsi K. Potluru, Sergey M. Plis, Jonathan Le Roux, Barak A. Pearlmutter, Vince D. Calhoun, and Thomas P. Hayes.
  Block Coordinate Descent for Sparse NMF.
  In First International Conference on Learning Representations (ICLR 2013) Scottsdale, Arizona, USA, May 2-4, 2013. arXiv:1301.3527
• Oleksandr Manzyuk.
  A Simply Typed Lambda-Calculus of Forward Automatic Differentiation.
  In 28th Conference on the Mathematical Foundations of Programming Semantics (MFPS XXVIII), Bath, United Kingdom, June 6-9, 2012. doi:10.1016/j.entcs.2012.08.017
• Alexey Radul, Barak A. Pearlmutter, and Jeffrey Mark Siskind.
  AD in Fortran, Part 2: Implementation via Prepreprocessor.
  Advances in Automatic Differentiation, Lecture Notes in Computational Science and Engineering, Springer, 2012. arXiv:1203.1450
• Míriam R. García, Mark Verwoerd, Barak A. Pearlmutter, Peter E. Wellstead, and Richard H. Middleton.
  Deep Brain Stimulation may Reduce Tremor by Preferential Blockade of Slower Axons via Antidromic Activation.
  In Proceedings of the IEEE Conference on Decision and Control, Orlando, FL, pages 6481-6, Dec. 2011. doi:10.1109/CDC.2011.6160710
• Ruairí de Fréin, S. T. Rickard, and B. A. Pearlmutter.
  Constructing time-frequency dictionaries for source separation via time-frequency masking and source localisation.
  In 8th International Conference on Independent Component Analysis and Signal Separation (ICA-2009), Paraty, Brazil, Springer-Verlag LNCS 5441, pages 573-80, Mar. 2009. doi:10.1007/978-3-642-00599-2_72
• Barak A. Pearlmutter and Conor J. Houghton.
  A New Hypothesis for Sleep: Tuning for Criticality.
  Neural Computation 21(6):1622-41, June 2009. doi:10.1162/neco.2009.05-08-787
• Jeffrey Mark Siskind and Barak A. Pearlmutter.
  Nesting forward-mode AD in a functional framework.
  Higher Order and Symbolic Computation 21(4):361-76, 2008. doi:10.1007/s10990-008-9037-1
• Paul D. O'Grady and Barak A. Pearlmutter.
  Discovering Speech Phones Using Convolutive Non-negative Matrix Factorisation with a Sparseness Constraint.
  Neurocomputing 72(1-3):88-101, Dec. 2008. doi:10.1016/j.neucom.2008.01.033
• Barak A. Pearlmutter and Jeffrey Mark Siskind.
  Using programming language theory to make AD sound and efficient.
  In Proceedings of the 5th International Conference on Automatic Differentiation, Bonn, Germany, pages 79-90, Aug. 2008. doi:10.1007/978-3-540-68942-3_8
• Barak A. Pearlmutter and Jeffrey Mark Siskind.
  Reverse-Mode AD in a functional framework: Lambda the ultimate backpropagator.
  TOPLAS 30(2):1-36, Mar. 2008. doi:10.1145/1330017.1330018
• Paul D. O'Grady and Barak A. Pearlmutter.
  The LOST Algorithm: Finding Lines and Separating Speech Mixtures.
  EURASIP Journal on Advances in Signal Processing, 2008:784296, 2008. doi:10.1155/2008/784296
• F. Matthews, B. A. Pearlmutter, T. E. Ward, C. Soraghan, and C. Markham.
  Hemodynamics for Brain-Computer Interfaces: Optical correlates of control signals.
  IEEE Signal Processing Magazine 25(1):87-94, Jan. 2008. doi:10.1109/MSP.2007.909011
• Edmund C. Lalor, Simon P. Kelly, Barak A. Pearlmutter, Richard B. Reilly, and John J. Foxe.
  Isolating endogenous visuo-spatial attentional effects using the novel visual-evoked spread spectrum analysis (VESPA) technique.
  European Journal of Neuroscience 26(12):3536-42, 2007. doi:10.1111/j.1460-9568.2007.05968.x
• Edmund C. Lalor, Sherlyn Yeap, Richard B. Reilly, Barak A. Pearlmutter, and John J. Foxe.
  Dissecting the cellular contributions to early visual sensory processing deficits in schizophrenia using the VESPA evoked response.
  Schizophrenia Research 98(1-3):256-64, Jan. 2008. Epub: Nov. 2007. doi:10.1016/j.schres.2007.09.037
• Paul D. O'Grady and Barak A. Pearlmutter.
  Discovering convolutive speech phones using sparseness and nonnegativity.
  In Seventh International Conference on Independent Component Analysis (ICA-2007), London, UK, Springer-Verlag LNCS 4666, pages 520-7, Sep. 2007.
• Santiago Jaramillo and Barak A. Pearlmutter.
  Optimal coding predicts attentional modulation in neuronal systems.
  Neural Computation 19(5):1295-1312, 2007. doi:10.1162/neco.2007.19.5.1295
• Lucas C. Parra and Barak A. Pearlmutter.
  Illusory Percepts from Auditory Adaptation.
  Journal of the Acoustical Society of America 121(3):1632-41, Mar. 2007. doi:10.1121/1.2431346
• Jeffrey Mark Siskind and Barak A. Pearlmutter.
  First-Class Nonstandard Interpretations by Opening Closures.
  In Proceedings of the 2007 Symposium on Principles of Programming Languages (POPL 2007), Nice France, pages 71-6, Jan. 2007. doi:10.1145/1190216.1190230
• Barak A. Pearlmutter and Jeffrey Mark Siskind.
  Lazy Multivariate Higher-Order Forward-Mode AD.
  In Proceedings of the 2007 Symposium on Principles of Programming Languages (POPL 2007), Nice France, pages 155-60, Jan. 2007. doi:10.1145/1190215.1190242
• Edmund C. Lalor, Barak A. Pearlmutter, John J. Foxe, Richard B. Reilly, and Gary McDarby.
  Spread-Spectrum Intensity Modulation for Rapid Estimation of a Visually Evoked Potential.
  NeuroImage 32:1549-61, 2006.
• Hiroki Asari, Barak A. Pearlmutter, and Anthony M. Zador.
  Sparse Representations for the Cocktail Party Problem.
  Journal of Neuroscience 26(28):7477-90, 2006. doi:10.1523/JNEUROSCI.1563-06.2006
• Santiago Jaramillo and Barak A. Pearlmutter.
  Use your powers wisely: Resource allocation in parallel channels.
  In Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2006), Sep. 2006. doi:10.1109/MLSP.2006.275515
• Paul D. O'Grady and Barak A. Pearlmutter.
  Convolutive Non-Negative Matrix Factorisation with Sparseness Constraint.
  In Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2006), Sep. 2006 doi:10.1109/MLSP.2006.275588
• Barak A. Pearlmutter and Rasmus K. Olsson.
  Linear program differentiation for single-channel speech separation.
  In Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2006), Sep. 2006 doi:10.1109/MLSP.2006.275587
• Paul D. O'Grady, Barak A. Pearlmutter, and Scott T. Rickard.
  Survey of Sparse and Non-Sparse Methods in Source Separation.
  International Journal of Imaging Systems and Technology (IJIST) 15:18-33, 2005. doi:10.1002/ima.20035
• S. C. Jun and B. A. Pearlmutter.
  Fast Robust Subject-Independent Magnetoencephalographic Source Localization using an Artificial Neural Network.
  Human Brain Mapping 24(1):21-34, 2005. doi:10.1002/hbm.20068
• Paul D. O'Grady and Barak A. Pearlmutter.
  Soft-LOST: EM on a Mixture of Oriented Lines.
  In Independent Component Analysis and Blind Signal Separation (ICA2004), Granada, Spain, pages 430-436, Sep. 2004. doi:10.1007/978-3-540-30110-3_55
• Barak A. Pearlmutter and Anthony M. Zador.
  Monaural Source Separation Using Spectral Cues.
  In Independent Component Analysis and Blind Signal Separation (ICA2004), Granada, Spain, pages 478-485, Sep. 2004. doi:10.1007/978-3-540-30110-3_61
• Sung Chan Jun and Barak A. Pearlmutter.
  Subject-Independent Magnetoencephalographic Source Localization by a Multilayer Perceptron.
  In Advances in Neural Information Processing Systems 16, MIT Press, 2004.
• Santiago Jaramillo and Barak A. Pearlmutter.
  A normative model of attention: receptive field modulation.
  Neurocomputing 58-60:613-618, 2004. doi:10.1016/j.neucom.2004.01.103
• Sung Chan Jun, Barak A. Pearlmutter, and Guido Nolte.
  MEG source localization using an MLP with a distributed output representation.
  IEEE Transactions on Biomedical Engineering 50(6):786-789, 2003. doi:10.1109/TBME.2003.812154
• Lucas Parra, Chris Alvino, Akaysha Tang, Barak Pearlmutter, Nick Yeung, Allen Osman, and Paul Sajda.
  Single-trial detection in EEG and MEG: Keeping it linear.
  Neurocomputing 52-54:177-183, June 2003. doi:10.1016/S0925-2312(02)00821-4
• Guido Nolte, Till Sander, Andreas Lueschow, and Barak A. Pearlmutter.
  Nonlinear properties of human alpha rhythm.
  Submitted
• Akaysha C. Tang, Barak. A. Pearlmutter, Natalie A. Malaszenko, and Dan B. Phung.
  Independent Components of Magnetoencephalography: Single-Trial Response Time Estimation.
  NeuroImage 17: 1773–1789, 2002. doi:10.1006/nimg.2002.1320
• Sung Chan Jun, Barak A. Pearlmutter, and Guido Nolte.
  Fast accurate MEG source localization using a MLP trained with real brain noise.
  Physics in Medicine and Biology 47(14):2547-2560, 2002.
• Lucas Parra, Chris Alvino, Akaysha Tang, Barak Pearlmutter, Nick Yeung, Allen Osman, and Paul Sajda.
  Linear spatial integration for single trial detection in encephalography.
  NeuroImage 17(1):223-230, 2002. doi:10.1006/nimg.2002.1212
• G. Nolte, T. Sander, A. Lueschow, and B. A. Pearlmutter.
  Nonlinear time series analysis of human alpha rhythm.
  In 13th International Conference on Biomagnetism (BIOMAG 2002), Jena, Germany, Aug. 10-14, 2002.
• S. C. Jun, B. A. Pearlmutter, G. Nolte.
  Fast robust MEG source localization using MLPs.
  In 13th International Conference on Biomagnetism (BIOMAG 2002), Jena, Germany, Aug. 10-14, 2002.
• Akaysha C. Tang, Barak A. Pearlmutter, Natalie A. Malaszenko, Dan B. Phung, and Bethany C. Reeb.
  Independent Components of Magnetoencephalography: Localization.
  Neural Computation 14(8):1827-1858, 2002. doi:10.1162/089976602760128036
• Michael Zibulevsky, Pavel Kisilev, Yehoshua Y. Zeevi, and Barak A. Pearlmutter.
  Blind source separation via multinode sparse representation.
  In Advances in Neural Information Processing Systems 14. Morgan Kaufmann, 1049-1056, 2002.
• Michael Zibulevsky and Barak A. Pearlmutter.
  Blind Source Separation by Sparse Decomposition in a Signal Dictionary.
  Neural Computation 13(4):863-882, 2001.
• Akaysha C. Tang, Dan Phung, Barak A. Pearlmutter, and Robert Christner.
  Localization of Independent Components from Magnetoencephalography.
  In Proceedings of the International Workshop on Independent Component Analysis and Blind Signal Separation (ICA2000), Helsinki, Finland, pages 387-392, June 2000.
• Michael Zibulevsky and Barak A. Pearlmutter.
  Second Order Blind Source Separation by Recursive Splitting of Signal Subspaces.
  In Proceedings of the International Workshop on Independent Component Analysis and Blind Signal Separation (ICA2000), Helsinki, Finland, pages 489-491, June 2000.
• Michael Zibulevsky and Barak A. Pearlmutter.
  Blind separation of sources with sparse representations in a given signal dictionary.
  In Proceedings of the International Workshop on Independent Component Analysis and Blind Signal Separation (ICA2000), Helsinki, Finland, pages 181-186, June 2000.
• Akaysha C. Tang, Barak A. Pearlmutter, Michael Zibulevsky, Tim A. Hely, and Michael P. Weisend.
  An MEG study of response latency and variability in the human visual system during a visual-motor integration task.
  In Advances in Neural Information Processing Systems 12. Morgan Kaufmann, 185-191, 2000.
• Gary W. Flake and Barak A. Pearlmutter.
  Differentiation functions of the Jacobian with respect to the weights.
  In Advances in Neural Information Processing Systems 12. Morgan Kaufmann, 435-441, 2000.
• Akaysha C. Tang, Barak A. Pearlmutter, Michael Zibulevsky, and Scott A. Carter.
  Blind source separation of multichannel neuromagnetic responses.
  Neurocomputing 32-33:1115-1120, 2000. doi:10.1016/S0925-2312(00)00286-1
• C. Warrender and S. Forrest and B. A. Pearlmutter.
  Detecting intrusions using system calls: Alternative data models.
  In IEEE Symposium on Security and Privacy, Oakland, California, USA, May 9-12, 1999. doi:10.1109/SECPRI.1999.766910
• Kevin J. Lang, Barak A. Pearlmutter, and Rodney A. Price.
  Results of the Abbadingo One DFA Learning Competition and a New Evidence-Driven State Merging Algorithm.
  In Fourth International Colloquium on Grammatical Inference (ICGI), Ames, Iowa, USA, Springer LNCS Vol. 1433, pages 1-12, 1998. doi:10.1007/BFb0054059
• Barak A. Pearlmutter and Lucas C. Parra.
  Maximum Likelihood Blind Source Separation: A Context-Sensitive Generalization of ICA.
  In Advances in Neural Information Processing Systems 9. MIT Press, 1997.
• Barak A. Pearlmutter and Lucas C. Parra.
  A context-sensitive generalization of ICA.
  In 1996 International Conference on Neural Information Processing, Hong Kong, Sep. 1996.
• Barak A. Pearlmutter.
  Doing the twist: Diagonal meshes are isomorphic to twisted toroidal meshes.
  IEEE Transactions on Computers 45(6), June 1996. doi:10.1109/12.506434
• Anthony M. Zador and Barak A. Pearlmutter.
  VC dimension of an integrate and fire neuron model.
  Neural Computation 8(3):611-624, 1996. doi:10.1162/neco.1996.8.3.611
• Anthony M. Zador and Barak A. Pearlmutter.
  VC dimension of an integrate and fire neuron model.
  In Ninth Conference on Computational Learning Theory, Desenzano del Garda, Italy, June 28-July 1, 1996.
• Barak A. Pearlmutter.
  Garbage collection with pointers to single cells.
  Communications of the ACM 39(12):202-206, Dec. 1996.
• Barak A. Pearlmutter.
  Gradient calculation for dynamic recurrent neural networks: a survey.
  IEEE Transactions on Neural Networks 6(5):1212-1228, 1995. doi:10.1109/72.410363
• Barak A. Pearlmutter.
  Time-skew Hebb rule in a nonisopotential neuron.
  Neural Computation 7(4):706-712, 1995. doi:10.1162/neco.1995.7.4.706
• Barak A. Pearlmutter.
  Fast exact multiplication by the Hessian.
  Neural Computation 6(1):147-160, 1994. doi:10.1162/neco.1994.6.1.147
• Joe Kilian, Kevin J. Lang, and Barak A. Pearlmutter.
  Playing the matching-shoulders lob-pass game with logarithmic regret.
  In Seventh Annual ACM Workshop on Computational Learning Theory, New Brunswick, NJ, pages 159-164, July 1994.
• Yann LeCun, Patrice Y. Simard, and Barak A. Pearlmutter.
  Automatic learning rate maximization by on-line estimation of the Hessian's eigenvectors.
  In Advances in Neural Information Processing Systems 5, Morgan Kaufmann, pages 156-163, 1993.
• Barak A. Pearlmutter.
  Gradient descent: Second-order momentum and saturating error.
  In Advances in Neural Information Processing Systems 4, Morgan Kaufmann, pages 887-894, 1992.
• Barak A. Pearlmutter and Ronald Rosenfeld.
  Chaitin-Kolmogorov complexity and generalization in neural networks.
  In Advances in Neural Information Processing Systems 3, Morgan Kaufmann, pages 925-931, 1991.
• Barak A. Pearlmutter.
  Two new learning procedures for recurrent networks.
  Neural Network Review 3(3):99-101, 1990.
• Barak A. Pearlmutter.
  Learning state space trajectories in recurrent neural networks.
  Neural Computation 1(2):263-269, 1989. doi:10.1109/IJCNN.1989.118724
• Kenneth Y. Goldberg and Barak A. Pearlmutter.
  Using a neural network to learn the dynamics of the CMU direct-drive arm II.
  In Advances in Neural Information Processing Systems I, Morgan Kaufmann, pages 356-363, 1989.
• Kevin J. Lang and Barak A. Pearlmutter.
  Oaklisp: an object-oriented dialect of Scheme.
  Lisp and Symbolic Computation 1(1):39-51, May 1988.
• Kevin J. Lang and Barak A. Pearlmutter.
  Oaklisp: an object-oriented Scheme with first class types.
  In ACM Conference on Object-Oriented Systems, Programming, Languages and Applications, pages 30-37, Sep. 1986. doi:10.1145/28697.28701

Book chapters

• E. C. Lalor, B. A. Pearlmutter, and J. J. Foxe.
  Reverse Correlation and the VESPA Method.
  In T. C. Handy (editor), Brain Signal Analysis: Advances in Neuroelectric and Neuromagnetic Methods, chapter 1. MIT Press: Cambridge, MA, 2009. ISBN 978-0-262-01308-6.
• H. Asari, R. K. Olsson, B. A. Pearlmutter, and A. M. Zador.
  Sparsification for monaural source separation.
  In S. Makino, T.-W. Lee, and H. Sawada (eds), Blind Speech Separation, chapter 14. Springer-Verlag, 2007. ISBN 978-1-4020-6478-4.
• Yaroslav O. Halchenko, Stephen José Hanson and Barak A. Pearlmutter.
  Multimodal Integration: fMRI, MRI, EEG, MEG.
  In L. Landini, V. Positano and M. F. Santarelli (eds), Advanced Image Processing in Magnetic Resonance Imaging, pages 223-265, Dekker, 2005. ISBN 0824725425.
• A. C. Tang and B. A. Pearlmutter.
  Independent Components of Magnetoencephalography: Localization and Single-Trial Response Onset Detection.
  In Z. L. Lu and L. Kaufman (eds), Magnetic Source Imaging of the Human Brain, Lawrence Erlbaum and Associates, 2003.
• Akaysha C. Tang and Barak A. Pearlmutter.
  Independent Components of Magnetoencephalography: Localization.
  In F. T. Sommer and A. Wichert (eds), Exploratory Analysis and Data Modelling in Functional Neuroimaging, MIT Press, chapter 7, pages 129-162, 2002.
• M. Zibulevsky, B. A. Pearlmutter, P. Bofill, and P. Kisilev.
  Blind source separation by sparse decomposition in a signal dictionary.
  In S. J. Roberts and R. M. Everson (eds), Independent Components Analysis: Principles and Practice, pages 181-208, Cambridge University Press, 2001.
• Barak A. Pearlmutter and Anthony M. Zador.
  Sparse matrix methods for modeling single neurons.
  In C. Koch (editor), Biophysics of Computation: Information Processing in Single Neurons, Oxford University Press, 1999.
• Barak A. Pearlmutter and Kevin J. Lang.
  The implementation of Oaklisp.
  In P. Lee (editor), Topics in Advanced Language Implementation, MIT Press, pages 189-215, 1991.

Other conference proceedings

• Atılım Güneş Baydin and Barak A. Pearlmutter.
  Automatic Differentiation of Algorithms for Machine Learning.
  In AutoML Workshop at the International Conference on Machine Learning (ICML 2014), Beijing, China, June 26, 2014. arXiv:1404.7456
• Míriam R. García, Barak A. Pearlmutter, Peter E. Wellstead, Mark Verwoerd, and Richard H. Middleton.
  A slow axon antidromic blockade hypothesis for tremor reduction via Deep Brain Stimulation.
  In 16th Yale Workshop on Learning and Adaptive Systems, pages 1-6, New Haven, CT, USA, June 5-7, 2013.
• Ruairí de Fréin, Scott Rickard, and Barak Pearlmutter.
  Sparse Multichannel Source Localisation and Separation.
  In IMA International Conference on Mathematics in Signal Processing, The Royal Agricultural College, Cirencester, UK, Dec. 2008.
• C. Soraghan, F. Matthews, C. Markham, B. A. Pearlmutter, R. O'Neill, and T. E. Ward.
  A 12-channel, real- time near-infrared spectroscopy instrument for brain-computer interface applications.
  In 30th Annual International IEEE EMBS Conference, pages 5648-51, Vancouver, British Columbia, Canada, IEEE Press, Aug. 20-24, 2008.
• F. Matthews, C. Soraghan, T. E. Ward, C. Markham, and B. A. Pearlmutter.
  Software platform for rapid prototyping of NIRS brain computer interfacing techniques.
  In 30th Annual International IEEE EMBS Conference, pages 4840-3, Vancouver, British Columbia, Canada, IEEE Press, Aug. 20-24, 2008.
• E. C. Lalor, R. B. Reilly, B. A. Pearlmutter, and J. J. Foxe.
  A spectrum of colors: Investigating the temporal frequency characteristics of the human visual system using a system identification approach.
  In Proceedings of the IEEE Engineering in Medicine and Biology Society, 1:3720-3, 2006. doi:10.1109/IEMBS.2006.259688
• C. Soraghan, F. Matthews, D. Kelly, T. Ward, C. Markham, B. A. Pearlmutter, and R. O'Neill.
  A dual-channel optical brain-computer interface in a gaming environment.
  In Proceedings of the 9th International Conference on Computer Games: AI, Animation, Mobile, Educational and Serious Games, Dublin, Ireland, pages 35-9, Nov. 2006.
• Jeffrey Mark Siskind and Barak A. Pearlmutter.
  Perturbation Confusion and Referential Transparency: Correct Functional Implementation of Forward-Mode AD.
  In Proceedings of the 17th International Workshop on Implementation and Application of Functional Languages (IFL2005), Dublin, Ireland, Sep. 19-21, 2005.
• Barak A. Pearlmutter and Hiroki Asari and Anthony M. Zador.
  Neuronal Predictions of Sparse Linear Representations.
  Forum Acusticum, Budapest, Hungary, Aug. 29-Sep. 2, 2005.
• Roderick Murray-Smith and Barak A. Pearlmutter.
  Transformations of Gaussian Process Priors.
  In J. Winkler, N. Lawrence, and M. Niranjan (eds), Machine Learning Workshop, Springer-Verlag LNAI 3635, pages 110-125, 2005.
• Paul D. O'Grady and Barak A. Pearlmutter.
  Hard-LOST: Modified k-Means for Oriented Lines.
  In Proceedings of the Irish Signals and Systems Conference (ISSC-2004), Belfast, Northern Ireland, UK, Jun 30-Jul 2, 2004.
• Jian Qing Shi, Roderick Murray-Smith, D. Mike Titterington and Barak A. Pearlmutter.
  Filtered Gaussian Processes for Learning with Large Data-Sets.
  In Switching and Learning in Feedback Systems: European Summer School on Multi-Agent Control, Maynooth, Ireland, Springer-Verlag LNCS 3355, pages 128-139, 2003. doi:10.1007/978-3-540-30560-6_5
• B. A. Pearlmutter and Vamsi K. Potluru.
  Sparse Separation: Principles and Tricks.
  Proc. SPIE 5102, Independent Component Analyses, Wavelets, and Neural Networks, pages 1-4, Apr. 2003. doi:10.1117/12.502473
• B. A. Pearlmutter and S. Jaramillo.
  Progress in Blind Separation of Magnetoencephalographic Data.
  Proc. SPIE 5102, Independent Component Analyses, Wavelets, and Neural Networks, pages 129-134, Apr. 2003. doi:10.1117/12.502478
• Lucas Parra, Chris Alvino, Akaysha Tang, Barak Pearlmutter, Nick Yeung, Allen Osman, and Paul Sajda.
  Linear spatial weighting for single trial detection in encephalography.
  Computational Neuroscience Meeting, Chicago, July 2002.
• Karen G. Haines, Barak A. Pearlmutter, John A. Moya, Kim Edlund, and Thomas P. Caudell.
  Visualizing communication between neurons in the Lamina Ganglionaris of Musca domestica.
  In International Joint Conference on Neural Networks (IJCNN 2000), Como, Italy, July 24-27, 2000. doi:10.1109/IJCNN.2000.861280
• Anthony M. Zador and Barak A. Pearlmutter.
  The discriminative power of a dynamical model neuron.
  In R. Greiner, T. Petsche, and S. J. Hanson (eds), Computational Learning Theory and Natural Learning Systems: Volume IV, MIT Press, pages 211-225, 1997.
• Akaysha C. Tang, Chun X. Falk, Lawrence B. Cohen, Jian Y. Wu, Barak A. Pearlmutter, and Hans Peter Hoepp.
  Response reliability of the neuronal population of the aplysia abdominal ganglion during the gill-withdrawal reflex.
  In International Joint Conference on Neural Networks, Beijing, PRC, IEEE Press, Nov. 1992.
• Barak A. Pearlmutter.
  Temporally continuous vs. clocked networks.
  In Neural Networks in Robotics, Kluwer Academic Publishers, pages 237-252, 1993. doi:10.1007/978-1-4615-3180-7_14
• John B. Hampshire, II and Barak A. Pearlmutter.
  Equivalence proofs for multi-layer perceptron classifiers and the Bayesian discriminant function.
  In Connectionist Models: Proceedings of the 1990 Summer School, Morgan Kaufmann, pages 159-172, 1990.
• Barak A. Pearlmutter.
  Learning state space trajectories in recurrent neural networks.
  In Proceedings of the 1988 Connectionist Models Summer School, Morgan Kaufmann, pages 113-117, 1989.
• Barak A. Pearlmutter.
  Learning state space trajectories in recurrent neural networks.
  In International Joint Conference on Neural Networks (IJCNN), Washington DC, IEEE Press, volume 2, pages 365-372, June 18-22, 1989. doi:10.1109/IJCNN.1989.118724
• Barak A. Pearlmutter and Geoffrey E. Hinton.
  G-maximization: an unsupervised learning procedure.
  In Snowbird Conference on Neural Networks for Computing, number 151 in AIP conference proceedings, American Institute of Physics, pages 333-338, 1986.

Technical reports

• V. K. Potluru, J. LeRoux, B. A. Pearlmutter, J. R. Hershey, and M. E. Brand.
  Coordinate descent for mixed-norm NMF.
  Technical Report TR2013-130, Mitsubishi Electric Research Laboratories, at NIPS-2013 Workshop, Dec. 2013.
• Andrei Barbu, N. Siddharth, Caiming Xiong, Jason J. Corso, Christiane D. Fellbaum, Catherine Hanson, Stephen José Hanson, Sébastien Hélie, Evguenia Malaia, Barak A. Pearlmutter, Jeffrey Mark Siskind, Thomas Michael Talavage, and Ronnie B. Wilbur.
  The Compositional Nature of Verb and Argument Representations in the Human Brain.
  arXiv:1306.2293
• Oleksandr Manzyuk, Barak A. Pearlmutter, Alexey Andreyevich Radul, David R. Rush, and Jeffrey Mark Siskind.
  Confusion of Tagged Perturbations in Forward Automatic Differentiation of Higher-Order Functions.
  arXiv:1211.4892
• Alexey Radul and Barak A. Pearlmutter and Jeffrey Mark Siskind.
  AD in Fortran, Part 1: Design.
  arXiv:1203.1448
• Jeffrey Mark Siskind and Barak A. Pearlmutter.
  Using Polyvariant Union-Free Flow Analysis to Compile a Higher-Order Functional-Programming Language with a First-Class Derivative Operator to Efficient Fortran-like Code.
  School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA, Jan. 2008. TR-ECE-08-01
• Jeffrey Mark Siskind and Barak A. Pearlmutter.
  Putting the Automatic Back into AD: Part I, What's Wrong.
  School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA, Jan. 2008. TR-ECE-08-02
• Barak A. Pearlmutter and Jeffrey Mark Siskind.
  Putting the Automatic Back into AD: Part II, Dynamic, Automatic, Nestable, and Fast.
  School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA, Jan. 2008. TR-ECE-08-03
• Barak A. Pearlmutter.
  Bounds on Query Convergence.
  arXiv:cs.LG/0511088
• R. Murray-Smith and Barak A. Pearlmutter.
  Transformations of Gaussian Process priors.
  DCS Technical Report TR-2003-149, Department of Computing Science, Glasgow University, June 2003. TR-2003-149
• Sung Chan Jun, Barak A. Pearlmutter, and Guido Nolte.
  Realtime MEG source localization with realistic noise.
  University of New Mexico, UNM TR-CS-2001-22.
• P. Kisilev, M. Zibulevsky, Y. Y. Zeevi, and B. A. Pearlmutter.
  Multiresolution framework for blind source separation.
  Department of Electrical Engineering, Technion-Israel Institute of Technology, 2000.
• Michael Zibulevsky and Barak A. Pearlmutter.
  Blind Source Separation by Sparse Decomposition.
  University of New Mexico Technical Report No. CS99-1. Albuquerque, NM, July 1999.
• Barak A. Pearlmutter.
  An Investigation of the Gradient Descent Process in Neural Networks.
  Technical Report CMU-CS-96-114, PhD Thesis, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, Jan. 1996.
• Barak A. Pearlmutter.
  Radar project results: March-September 1995.
  Technical Report SCR-96-TR-554, Siemens Corporate Research, Princeton, NJ, 1996.
• Barak A. Pearlmutter and Scott T. Rickard, Jr.
  Linear compression of the strips database
  Technical Report SCR-95-TR-537, Siemens Corporate Research, Princeton, NJ, 1995.
• Barak A. Pearlmutter and Leonid Gurvits.
  Relating egomotion and image evolution.
  Technical Report SCR-95-TR-536, Siemens Corporate Research, Princeton, NJ, 1995.
• Anthony M. Zador and Barak A. Pearlmutter.
  Efficient computation of sparse elements of the inverse of a sparse near-tridiagonal matrix with application to the nerve equation.
  Technical Report OGI-CSE-93-003, Oregon Graduate Institute of Science & Technology, Department of Computer Science and Engineering, Portland, OR, Mar. 1993.
• Barak A. Pearlmutter.
  Fast exact multiplication by the Hessian.
  Technical Report OGI-CSE 93-002, Oregon Graduate Institute of Science & Technology, Department of Computer Science and Engineering, Portland, OR, Mar. 1993.
• Barak A. Pearlmutter.
  Dynamic recurrent neural networks.
  Technical Report CMU-CS-90-196, Carnegie Mellon University School of Computer Science, Pittsburgh, PA, Dec. 1990.
• Kenneth Y. Goldberg and Barak A. Pearlmutter.
  Using a neural network to learn the dynamics of the CMU Direct-Drive Arm II.
  Technical Report CMU-CS-88-160, Carnegie Mellon University, 1988.
• Barak A. Pearlmutter.
  Learning state space trajectories in recurrent neural networks.
  Technical Report CMU-CS-88-191, Department of Computer Science, Carnegie Mellon University, Pittsburgh, PA, 1988.

Abstracts

• Atılım Güneş Baydin and Barak A. Pearlmutter.
  DiffSharp: Automatic Differentiation Library.
  Poster at Deep Learning Summer School 2015, Centre de recherches mathématiques, University of Montreal, August 3, 2015.
• Atılım Güneş Baydin and Barak A. Pearlmutter.
  DiffSharp: Automatic Differentiation Library.
  Poster at Workshop on Machine Learning Open Source Software, International Conference on Machine Learning, July 10, 2015.
• Míriam R. García, Barak A. Pearlmutter, Peter E. Wellstead, Mark Verwoerd, and Richard H. Middleton.
  A functional mechanism for deep brain stimulation in Parkinson's disease: The slow axon blockade hypothesis.
  Movement Disorders 27:491 (Suppl 1), 2012.
• Barak A. Pearlmutter and Conor J. Houghton.
  Tuning for Criticality: A New Hypothesis for Sleep.
  Poster at COSYNE 2007, Salt Lake City, Utah, USA, Feb 22-24, 2007.
• Edmund C. Lalor, Richard B. Reilly, Barak A. Pearlmutter, and John J. Foxe.
  Investigating Multisensory Integration using Spread Spectrum Stimulation.
  Poster at 7th Annual Meeting of the International Multisensory Research Forum, School of Psychology/Institute of Neuroscience, University of Dublin Trinity College, June 18-21, 2006.
• Santiago Jaramillo and Barak A. Pearlmutter.
  Exploring the attentional modulation of neural codes.
  Poster at Computational and Systems Neuroscience Workshop, Cold Spring Harbor Laboratories, Mar. 2004.
• Barak A. Pearlmutter and Anthony M. Zador.
  Monaural Source Separation using Spectral Cues.
  Poster at Computational and Systems Neuroscience Workshop, Cold Spring Harbor Laboratories, Mar. 2004.
• S. Jaramillo and B. A. Pearlmutter.
  A normative model of attention: receptive field modulation.
  Society for Neuroscience Abstracts 33(180.13), 2003.
• B. A. Pearlmutter and S. Jaramillo.
  Brightness Illusions as Optimal Percepts.
  Society for Neuroscience Abstracts 33(698.13), 2003.
• S. C. Jun, B. A. Pearlmutter, and G. Nolte.
  Fast Subject Independent Magnetoencephalographic (MEG) Source Localization using an Artificial Neural Network.
  Society for Neuroscience Abstracts 32, 2002.
• Barak A. Pearlmutter.
  Algorithmic Differentiation, Functional Programming, and Iterate-to-Fixedpoint.
  The Learning Workshop. Snowbird Utah, April 2-5, 2002.
• Santiago Jaramillo and Barak A. Pearlmutter and Akaysha C. Tang and Guido Nolte.
  Relationship Between the Phase of Alpha-Band Oscillation and Single-Trial Visually Evoked Responses.
  Society for Neuroscience Abstracts 31(821.1), 2001.
• Sung Chan Jun, Barak A. Pearlmutter, and Guido Nolte.
  MEG source localization using an MLP.
  Inverse Problems in Engineering Symposium, June 14-16, 2001.
• Lucas Parra, Akaysha Tang, Barak Pearlmutter, Zuohau Zhang, and Paul Sajda.
  Predicting motor commands using magnetoencephalography (MEG).
  Cognitive Neuroscience Annual Meeting, F-30, March 25-27, 2001.
• A. C. Tang, D. B. Phung and B. A. Pearlmutter.
  Direct measurement of interhemispherical transfer time (IHTT) for natural somatosensory stimulation during voluntary movement using MEG and blind source separation.
  Society for Neuroscience Abstracts 30(9195), 2000.
• D. B. Phung, A. C. Tang, B. A. Pearlmutter and R. Christner.
  Localization of MEG components recovered by blind source separation.
  Society for Neuroscience Abstracts 30(9196), 2000.
• S. A. Carter, A. C. Tang, B. A. Pearlmutter, L. K. Anderson, C. J. Aine and R. Christner.
  Coactivation of visual and auditory pathways induces changes in the timing of evoked responses in populations of neurons: an MEG study.
  Society for Neuroscience Abstracts 30(9197), 2000.
• Barak A. Pearlmutter and Monica Rogati.
  Learn to pay attention, young network!
  Snowbird Workshop on Machines that Learn, April 2000. Poster.
• Barak A. Pearlmutter, Akaysha C. Tang, Michael Zibulevsky, Tim A. Hely, and Michael P. Weisend.
  An MEG study of response latency and variability in the human visual system during a visual-motor integration task.
  Society for Neuroscience Abstracts 29(766.8), 1999.
• Lucas C. Parra and Barak A. Pearlmutter.
  Maximal information transfer in a spiking neuron.
  Society for Neuroscience Abstracts 21(480.7), 1995.
• Lucas C. Parra and Barak A. Pearlmutter.
  Maximal information transfer in a spiking neuron.
  Snowbird Workshop on Neural Networks for Computing, April 1995. Poster.
• Anthony M. Zador and Barak A. Pearlmutter.
  Efficient matrix methods in the analysis of electrotonic structure in single neurons.
  Snowbird Workshop on Neural Networks for Computing, Apr. 1994.
• Kevin J. Lang and Barak A. Pearlmutter.
  Playing the matching-shoulders lob-pass game with logarithmic regret.
  Snowbird Workshop on Neural Networks for Computing, Apr. 1994. Poster.
• Akaysha C. Tang, Chun X. Falk, Lawrence B. Cohen, Jian Y. Wu, Barak A. Pearlmutter, and Hans Peter Hoepp.
  Multicellular optical recording reveals neuronal population with broad spectrum of response probability.
  Society for Neuroscience Abstracts 18, 1992.
• Barak A. Pearlmutter and Thomas H. Brown.
  Hebbian learning is jointly controlled by electrotonic and input structure.
  Society for Neuroscience Abstracts 18(567.23), 1992.
• Barak A. Pearlmutter and Thomas H. Brown.
  Hebbian learning is jointly controlled by electrotonic and input structure.
  Poster at Snowbird Workshop on Neural Networks for Computing, Apr. 1992.
• Barak A. Pearlmutter.
  Generalization in perceptrons with noisy inputs.
  Poster at Computational Learning Theory and Natural Learning Systems workshop, Sep. 1990.
• Barak A. Pearlmutter.
  Redundancy and correctness.
  Poster at Snowbird Workshop on Neural Networks for Computing, Apr. 1990.
• Barak A. Pearlmutter.
  Learning state space trajectories in recurrent neural networks.
  Talk at Snowbird Workshop on Neural Networks for Computing, Apr. 1989.

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