The SCEAS System
Navigation Menu
Introduction
Collection Based
Clustering
Ranking
Paper Based
Journals
Conferences
DB Status
Statistics
Search

Search the dblp DataBase

Title:
Author:
Wolfgang Maass: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Zhixiang Chen, Wolfgang Maass
    A Solution of the Credit Assignment Problem in the Case of Learning Rectangles (Abstract). [Citation Graph (0, 0)][DBLP]
    AII, 1992, pp:26-34 [Conf]
  2. Wolfgang Maass
    On the Relevance of Time in Neural Computation and Learning. [Citation Graph (0, 0)][DBLP]
    ALT, 1997, pp:364-384 [Conf]
  3. Prashant Joshi, Wolfgang Maass
    Movement Generation and Control with Generic Neural Microcircuits. [Citation Graph (0, 0)][DBLP]
    BioADIT, 2004, pp:258-273 [Conf]
  4. Wolfgang Maass, Robert A. Legenstein, Henry Markram
    A New Approach towards Vision Suggested by Biologically Realistic Neural Microcircuit Models. [Citation Graph (0, 0)][DBLP]
    Biologically Motivated Computer Vision, 2002, pp:282-293 [Conf]
  5. Martin Dietzfelbinger, Wolfgang Maass
    two Lower Bound Arguments with "Inaccessible" Numbers. [Citation Graph (0, 0)][DBLP]
    Structure in Complexity Theory Conference, 1986, pp:163-183 [Conf]
  6. Wolfgang Maass, Georg Schnitger
    An Optimal Lower Bound for Turing Machines with One Work Tape and a Two- way Input Tape. [Citation Graph (0, 0)][DBLP]
    Structure in Complexity Theory Conference, 1986, pp:249-264 [Conf]
  7. Wolfgang Maass, Theodore A. Slaman
    The Complexity Types of Computable Sets. [Citation Graph (0, 0)][DBLP]
    Structure in Complexity Theory Conference, 1989, pp:231-239 [Conf]
  8. Peter Auer, Stephen Kwek, Wolfgang Maass, Manfred K. Warmuth
    Learning of Depth Two Neural Networks with Constant Fan-In at the Hidden Nodes (Extended Abstract). [Citation Graph (0, 0)][DBLP]
    COLT, 1996, pp:333-343 [Conf]
  9. Peter Auer, Philip M. Long, Wolfgang Maass, Gerhard J. Woeginger
    On the Complexity of Function Learning. [Citation Graph (0, 0)][DBLP]
    COLT, 1993, pp:392-401 [Conf]
  10. William J. Bultman, Wolfgang Maass
    Fast Identification of Geometric Objects with Membership Queries. [Citation Graph (0, 0)][DBLP]
    COLT, 1991, pp:337-353 [Conf]
  11. Zhixiang Chen, Wolfgang Maass
    On-line Learning of Rectangles. [Citation Graph (0, 0)][DBLP]
    COLT, 1992, pp:16-28 [Conf]
  12. Wolfgang Maass
    On-Line Learning with an Oblivious Environment and the Power of Randomization. [Citation Graph (0, 0)][DBLP]
    COLT, 1991, pp:167-175 [Conf]
  13. Wolfgang Maass
    Efficient Agnostic PAC-Learning with Simple Hypothesis. [Citation Graph (0, 0)][DBLP]
    COLT, 1994, pp:67-75 [Conf]
  14. Wolfgang Maass, Michael Schmitt
    On the Complexity of Learning for a Spiking Neuron (Extended Abstract). [Citation Graph (0, 0)][DBLP]
    COLT, 1997, pp:54-61 [Conf]
  15. Wolfgang Maass, György Turán
    On the Complexity of Learning from Counterexamples and Membership Queries (abstract). [Citation Graph (0, 0)][DBLP]
    COLT, 1990, pp:391- [Conf]
  16. Wolfgang Maass
    A Cognitive Model for the Process of Multimodal, Incremental Route Descriptions. [Citation Graph (0, 0)][DBLP]
    COSIT, 1993, pp:1-13 [Conf]
  17. Wolfgang Maass
    How Spatial Information Connects Visual Perception and Natural Language Generation in Dynamic Environments: Towards a Computational Model. [Citation Graph (0, 0)][DBLP]
    COSIT, 1995, pp:223-240 [Conf]
  18. Wolfgang Maass, Gerald Steinbauer, Roland Koholka
    Autonomous Fast Learning in a Mobile Robot. [Citation Graph (0, 0)][DBLP]
    Sensor Based Intelligent Robots, 2000, pp:345-356 [Conf]
  19. Thomas Natschläger, Wolfgang Maass
    Fast analog computation in networks of spiking neurons using unreliable synapses. [Citation Graph (0, 0)][DBLP]
    ESANN, 1999, pp:417-422 [Conf]
  20. Wolfgang Maass, Theodore A. Slaman
    Extensional Properties of Sets of Time Bounded Complexity (Extended Abstract). [Citation Graph (0, 0)][DBLP]
    FCT, 1989, pp:318-326 [Conf]
  21. Noga Alon, Wolfgang Maass
    Meanders, Ramsey Theory and Lower Bounds for Branching Programs [Citation Graph (0, 0)][DBLP]
    FOCS, 1986, pp:410-417 [Conf]
  22. András Hajnal, Wolfgang Maass, Pavel Pudlák, Mario Szegedy, György Turán
    Threshold circuits of bounded depth [Citation Graph (0, 0)][DBLP]
    FOCS, 1987, pp:99-110 [Conf]
  23. Wolfgang Maass, Georg Schnitger, Eduardo D. Sontag
    On the Computational Power of Sigmoid versus Boolean Threshold Circuits [Citation Graph (0, 0)][DBLP]
    FOCS, 1991, pp:767-776 [Conf]
  24. Wolfgang Maass, György Turán
    On the Complexity of Learning From Counterexamples (Extended Abstract) [Citation Graph (0, 0)][DBLP]
    FOCS, 1989, pp:262-267 [Conf]
  25. Wolfgang Maass, György Turán
    On the Complexity of Learning from Counterexamples and Membership Queries [Citation Graph (0, 0)][DBLP]
    FOCS, 1990, pp:203-210 [Conf]
  26. Wolfgang Maass, Andreas Filler
    Towards an Infrastructure for Semantically Annotated Physical Products. [Citation Graph (0, 0)][DBLP]
    GI Jahrestagung (2), 2006, pp:544-549 [Conf]
  27. Martin Dietzfelbinger, Wolfgang Maass
    The Complexity of Matrix Transposition on One-Tape Off-Line Turing Machines with Output Tape. [Citation Graph (0, 0)][DBLP]
    ICALP, 1988, pp:188-200 [Conf]
  28. Kei Uchizawa, Rodney J. Douglas, Wolfgang Maass
    Energy Complexity and Entropy of Threshold Circuits. [Citation Graph (0, 0)][DBLP]
    ICALP (1), 2006, pp:631-642 [Conf]
  29. Peter Auer, Harald Burgsteiner, Wolfgang Maass
    Reducing Communication for Distributed Learning in Neural Networks. [Citation Graph (0, 0)][DBLP]
    ICANN, 2002, pp:123-128 [Conf]
  30. Wolfgang Maass
    On the Computational Power of Neural Microcircuit Models: Pointers to the Literature. [Citation Graph (0, 0)][DBLP]
    ICANN, 2002, pp:254-258 [Conf]
  31. Peter Auer, Robert C. Holte, Wolfgang Maass
    Theory and Applications of Agnostic PAC-Learning with Small Decision Trees. [Citation Graph (0, 0)][DBLP]
    ICML, 1995, pp:21-29 [Conf]
  32. Wolfgang Maass, Manfred K. Warmuth
    Efficient Learning with Virtual Threshold Gates. [Citation Graph (0, 0)][DBLP]
    ICML, 1995, pp:378-386 [Conf]
  33. Wolfgang Maass
    Models for Fast Analog Computation with Spiking Neurons. [Citation Graph (0, 0)][DBLP]
    ICONIP, 1998, pp:187-188 [Conf]
  34. Wolfgang Maass
    On the Role of Time and Space in Neural Computation. [Citation Graph (0, 0)][DBLP]
    MFCS, 1998, pp:72-83 [Conf]
  35. Wolfgang Maass
    Spiking Neurons. [Citation Graph (0, 0)][DBLP]
    NC, 1998, pp:16-20 [Conf]
  36. Ajay Gupta, Wolfgang Maass
    Efficient Design of Boltzmann Machines. [Citation Graph (0, 0)][DBLP]
    NIPS, 1990, pp:825-831 [Conf]
  37. Robert A. Legenstein, Wolfgang Maass
    Foundations for a Circuit Complexity Theory of Sensory Processing. [Citation Graph (0, 0)][DBLP]
    NIPS, 2000, pp:259-265 [Conf]
  38. Robert A. Legenstein, Wolfgang Maass
    A Criterion for the Convergence of Learning with Spike Timing Dependent Plasticity. [Citation Graph (0, 0)][DBLP]
    NIPS, 2005, pp:- [Conf]
  39. Wolfgang Maass, Eduardo D. Sontag
    A Precise Characterization of the Class of Languages Recognized by Neural Nets under Gaussian and Other Common Noise Distributions. [Citation Graph (0, 0)][DBLP]
    NIPS, 1998, pp:281-287 [Conf]
  40. Wolfgang Maass, Pekka Orponen
    On the Effect of Analog Noise in Discrete-Time Analog Computations. [Citation Graph (0, 0)][DBLP]
    NIPS, 1996, pp:218-224 [Conf]
  41. Wolfgang Maass, Anthony M. Zador
    Dynamic Stochastic Synapses as Computational Units. [Citation Graph (0, 0)][DBLP]
    NIPS, 1997, pp:- [Conf]
  42. Wolfgang Maass
    Noisy Spiking Neurons with Temporal Coding have more Computational Power than Sigmoidal Neurons. [Citation Graph (0, 0)][DBLP]
    NIPS, 1996, pp:211-217 [Conf]
  43. Wolfgang Maass
    Neural Computation with Winner-Take-All as the Only Nonlinear Operation. [Citation Graph (0, 0)][DBLP]
    NIPS, 1999, pp:293-299 [Conf]
  44. Wolfgang Maass, Prashant Joshi, Eduardo D. Sontag
    Principles of real-time computing with feedback applied to cortical microcircuit models. [Citation Graph (0, 0)][DBLP]
    NIPS, 2005, pp:- [Conf]
  45. Wolfgang Maass, Robert A. Legenstein, Nils Bertschinger
    Methods for Estimating the Computational Power and Generalization Capability of Neural Microcircuits. [Citation Graph (0, 0)][DBLP]
    NIPS, 2004, pp:- [Conf]
  46. Wolfgang Maass
    Agnostic PAC-Learning of Functions on Analog Neural Nets. [Citation Graph (0, 0)][DBLP]
    NIPS, 1993, pp:311-318 [Conf]
  47. Wolfgang Maass
    On the Computational Complexity of Networks of Spiking Neurons. [Citation Graph (0, 0)][DBLP]
    NIPS, 1994, pp:183-190 [Conf]
  48. Wolfgang Maass
    On the Computational Power of Noisy Spiking Neurons. [Citation Graph (0, 0)][DBLP]
    NIPS, 1995, pp:211-217 [Conf]
  49. Wolfgang Maass, Thomas Natschläger, Henry Markram
    A Model for Real-Time Computation in Generic Neural Microcircuits. [Citation Graph (0, 0)][DBLP]
    NIPS, 2002, pp:213-220 [Conf]
  50. Thomas Natschläger, Wolfgang Maass
    Finding the Key to a Synapse. [Citation Graph (0, 0)][DBLP]
    NIPS, 2000, pp:138-144 [Conf]
  51. Thomas Natschläger, Wolfgang Maass
    Information Dynamics and Emergent Computation in Recurrent Circuits of Spiking Neurons. [Citation Graph (0, 0)][DBLP]
    NIPS, 2003, pp:- [Conf]
  52. Thomas Natschläger, Wolfgang Maass, Eduardo D. Sontag, Anthony M. Zador
    Processing of Time Series by Neural Circuits with Biologically Realistic Synaptic Dynamics. [Citation Graph (0, 0)][DBLP]
    NIPS, 2000, pp:145-151 [Conf]
  53. Dimitris Apostolou, Gregoris Mentzas, Andreas Abecker, Wolf-Christian Eickhoff, Wolfgang Maas, Panos Georgolios, Kostas Kafentzis, Sophia Kyriakopoulou
    Challenges and Directions in Knowledge Asset Trading. [Citation Graph (0, 0)][DBLP]
    PAKM, 2002, pp:549-564 [Conf]
  54. Dorit S. Hochbaum, Wolfgang Maass
    Approximation Schemes for Covering and Packing Problems in Robotics and VLSI. [Citation Graph (0, 0)][DBLP]
    STACS, 1984, pp:55-62 [Conf]
  55. András Hajnal, Wolfgang Maass, György Turán
    On the Communication Complexity of Graph Properties [Citation Graph (0, 0)][DBLP]
    STOC, 1988, pp:186-191 [Conf]
  56. Wolfgang Maass
    Quadratic Lower Bounds for Deterministic and Nondeterministic One-Tape Turing Machines (Extended Abstract) [Citation Graph (0, 0)][DBLP]
    STOC, 1984, pp:401-408 [Conf]
  57. Wolfgang Maass
    Bounds for the computational power and learning complexity of analog neural nets. [Citation Graph (0, 0)][DBLP]
    STOC, 1993, pp:335-344 [Conf]
  58. Wolfgang Maass, Georg Schnitger, Endre Szemerédi
    Two Tapes Are Better than One for Off-Line Turing Machines [Citation Graph (0, 0)][DBLP]
    STOC, 1987, pp:94-100 [Conf]
  59. Winfried Graf, Wolfgang Maass
    Constraint-basierte Verarbeitung graphischen Wissens. [Citation Graph (0, 0)][DBLP]
    Wissensbasierte Systeme, 1991, pp:243-253 [Conf]
  60. Klaus Sutner, Wolfgang Maass
    Motion Planning Among Time Dependent Obstacles. [Citation Graph (0, 0)][DBLP]
    Acta Inf., 1988, v:26, n:1/2, pp:93-122 [Journal]
  61. Wolfgang Maass
    From Vision to Multimodal Communication: Incremental Route Descriptions. [Citation Graph (0, 0)][DBLP]
    Artif. Intell. Rev., 1994, v:8, n:2-3, pp:159-174 [Journal]
  62. Wolfgang Maass, Georg Schnitger, Endre Szemerédi, György Turán
    Two Tapes Versus One for Off-Line Turing Machines. [Citation Graph (0, 0)][DBLP]
    Computational Complexity, 1993, v:3, n:, pp:392-401 [Journal]
  63. Wolfgang Maass
    Neural Computation: A Research Topic for Theoretical Computer Science? Some Thoughts and Pointers. [Citation Graph (0, 0)][DBLP]
    Bulletin of the EATCS, 2000, v:72, n:, pp:149-158 [Journal]
  64. Wolfgang Maass
    A Simple Model for Neural Computation with Firing Rates and Firing Correlations [Citation Graph (0, 0)][DBLP]
    Electronic Colloquium on Computational Complexity (ECCC), 2000, v:7, n:30, pp:- [Journal]
  65. Wolfgang Maass, Eduardo D. Sontag
    Neural Systems as Nonlinear Filters [Citation Graph (0, 0)][DBLP]
    Electronic Colloquium on Computational Complexity (ECCC), 2000, v:7, n:31, pp:- [Journal]
  66. Wolfgang Maass
    On the Computational Power of Winner-Take-All [Citation Graph (0, 0)][DBLP]
    Electronic Colloquium on Computational Complexity (ECCC), 2000, v:7, n:32, pp:- [Journal]
  67. Wolfgang Maass
    On Computation with Pulses [Citation Graph (0, 0)][DBLP]
    Electronic Colloquium on Computational Complexity (ECCC), 2000, v:7, n:38, pp:- [Journal]
  68. Peter Auer, Philip M. Long, Wolfgang Maass, Gerhard J. Woeginger
    On the Complexity of Function Learning [Citation Graph (0, 0)][DBLP]
    Electronic Colloquium on Computational Complexity (ECCC), 2000, v:7, n:50, pp:- [Journal]
  69. Peter Auer, Stephen Kwek, Wolfgang Maass, Manfred K. Warmuth
    Learning of Depth Two Neural Networks with Constant Fan-in at the Hidden Nodes [Citation Graph (0, 0)][DBLP]
    Electronic Colloquium on Computational Complexity (ECCC), 2000, v:7, n:55, pp:- [Journal]
  70. Robert A. Legenstein, Wolfgang Maass
    Optimizing the Layout of a Balanced Tree [Citation Graph (0, 0)][DBLP]
    Electronic Colloquium on Computational Complexity (ECCC), 2001, v:8, n:069, pp:- [Journal]
  71. Robert A. Legenstein, Wolfgang Maass
    Total Wire Length as a Salient Circuit Complexity Measure for Sensory Processing [Citation Graph (0, 0)][DBLP]
    Electronic Colloquium on Computational Complexity (ECCC), 2001, v:8, n:070, pp:- [Journal]
  72. Robert A. Legenstein, Wolfgang Maass
    Neural Circuits for Pattern Recognition with Small Total Wire Length [Citation Graph (0, 0)][DBLP]
    Electronic Colloquium on Computational Complexity (ECCC), 2001, v:8, n:071, pp:- [Journal]
  73. Wolfgang Maass, Henry Markram
    On the Computational Power of Recurrent Circuits of Spiking Neurons [Citation Graph (0, 0)][DBLP]
    Electronic Colloquium on Computational Complexity (ECCC), 2002, v:, n:022, pp:- [Journal]
  74. Wolfgang Maass
    Bounds for the Computational Power and Learning Complexity of Analog Neural Nets [Citation Graph (0, 0)][DBLP]
    Electronic Colloquium on Computational Complexity (ECCC), 1994, v:1, n:12, pp:- [Journal]
  75. Wolfgang Maass
    Neural Nets with Superlinear VC-Dimension [Citation Graph (0, 0)][DBLP]
    Electronic Colloquium on Computational Complexity (ECCC), 1994, v:1, n:17, pp:- [Journal]
  76. Wolfgang Maass
    Lower Bounds for the Computational Power of Networks of Spiking Neurons [Citation Graph (0, 0)][DBLP]
    Electronic Colloquium on Computational Complexity (ECCC), 1994, v:1, n:19, pp:- [Journal]
  77. Wolfgang Maass
    Agnostic PAC-Learning of Functions on Analog Neural Nets [Citation Graph (0, 0)][DBLP]
    Electronic Colloquium on Computational Complexity (ECCC), 1994, v:1, n:20, pp:- [Journal]
  78. David P. Dobkin, Dimitrios Gunopulos, Wolfgang Maass
    Computing the Maximum Bichromatic Discrepancy, with applications to Computer Graphics and Machine Learning [Citation Graph (0, 0)][DBLP]
    Electronic Colloquium on Computational Complexity (ECCC), 1994, v:1, n:25, pp:- [Journal]
  79. Wolfgang Maass
    Networks of Spiking Neurons: The Third Generation of Neural Network Models [Citation Graph (0, 0)][DBLP]
    Electronic Colloquium on Computational Complexity (ECCC), 1996, v:3, n:31, pp:- [Journal]
  80. Wolfgang Maass, Jörg P. Müller
    Preface to the Special Section on Software Agents. [Citation Graph (0, 0)][DBLP]
    Electronic Markets, 2003, v:13, n:1, pp:- [Journal]
  81. William J. Bultman, Wolfgang Maass
    Fast Identification of Geometric Objects with Membership Queries [Citation Graph (0, 0)][DBLP]
    Inf. Comput., 1995, v:118, n:1, pp:48-64 [Journal]
  82. Wolfgang Maass, Berthold Ruf
    On Computations with Pulses. [Citation Graph (0, 0)][DBLP]
    Inf. Comput., 1999, v:148, n:2, pp:202-218 [Journal]
  83. Wolfgang Maass, Michael Schmitt
    On the Complexity of Learning for Spiking Neurons with Temporal Coding. [Citation Graph (0, 0)][DBLP]
    Inf. Comput., 1999, v:153, n:1, pp:26-46 [Journal]
  84. Wolfgang Maass, Manfred K. Warmuth
    Efficient Learning With Virtual Threshold Gates. [Citation Graph (0, 0)][DBLP]
    Inf. Comput., 1998, v:141, n:1, pp:66-83 [Journal]
  85. Dorit S. Hochbaum, Wolfgang Maass
    Approximation Schemes for Covering and Packing Problems in Image Processing and VLSI [Citation Graph (0, 0)][DBLP]
    J. ACM, 1985, v:32, n:1, pp:130-136 [Journal]
  86. Dorit S. Hochbaum, Wolfgang Maass
    Fast Approximation Algorithms for a Nonconvex Covering Problem. [Citation Graph (0, 0)][DBLP]
    J. Algorithms, 1987, v:8, n:3, pp:305-323 [Journal]
  87. Noga Alon, Wolfgang Maass
    Meanders and Their Applications in Lower Bounds Arguments. [Citation Graph (0, 0)][DBLP]
    J. Comput. Syst. Sci., 1988, v:37, n:2, pp:118-129 [Journal]
  88. Martin Dietzfelbinger, Wolfgang Maass
    Lower Bound Arguments with "Inaccessible" Numbers. [Citation Graph (0, 0)][DBLP]
    J. Comput. Syst. Sci., 1988, v:36, n:3, pp:313-335 [Journal]
  89. David P. Dobkin, Dimitrios Gunopulos, Wolfgang Maass
    Computing the Maximum Bichromatic Discrepancy with Applications to Computer Graphics and Machine Learning. [Citation Graph (0, 0)][DBLP]
    J. Comput. Syst. Sci., 1996, v:52, n:3, pp:453-470 [Journal]
  90. András Hajnal, Wolfgang Maass, Pavel Pudlák, Mario Szegedy, György Turán
    Threshold Circuits of Bounded Depth. [Citation Graph (0, 0)][DBLP]
    J. Comput. Syst. Sci., 1993, v:46, n:2, pp:129-154 [Journal]
  91. Robert A. Legenstein, Wolfgang Maass
    Wire length as a circuit complexity measure. [Citation Graph (0, 0)][DBLP]
    J. Comput. Syst. Sci., 2005, v:70, n:1, pp:53-72 [Journal]
  92. Wolfgang Maass
    Editor's Foreword. [Citation Graph (0, 0)][DBLP]
    J. Comput. Syst. Sci., 1995, v:51, n:3, pp:339- [Journal]
  93. Wolfgang Maass, Henry Markram
    On the computational power of circuits of spiking neurons. [Citation Graph (0, 0)][DBLP]
    J. Comput. Syst. Sci., 2004, v:69, n:4, pp:593-616 [Journal]
  94. Wolfgang Maass, Theodore A. Slaman
    The Complexity Types of Computable Sets. [Citation Graph (0, 0)][DBLP]
    J. Comput. Syst. Sci., 1992, v:44, n:2, pp:168-192 [Journal]
  95. Wolfgang Maass
    On the Use of Inaccessible Numbers and Order Indiscernibles in Lower Bound Arguments for Random Access Machines. [Citation Graph (0, 0)][DBLP]
    J. Symb. Log., 1988, v:53, n:4, pp:1098-1109 [Journal]
  96. Wolfgang Maass
    Variations on Promptly Simple Sets. [Citation Graph (0, 0)][DBLP]
    J. Symb. Log., 1985, v:50, n:1, pp:138-148 [Journal]
  97. Wolfgang Maass
    The Uniform Regular Set Theorem in a-Recursion Theory. [Citation Graph (0, 0)][DBLP]
    J. Symb. Log., 1978, v:43, n:2, pp:270-279 [Journal]
  98. Wolfgang Maass
    Recursively Enumerable Generic Sets. [Citation Graph (0, 0)][DBLP]
    J. Symb. Log., 1982, v:47, n:4, pp:809-823 [Journal]
  99. Wolfgang Maass
    On the Orbits of Hyperhypersimple Sets. [Citation Graph (0, 0)][DBLP]
    J. Symb. Log., 1984, v:49, n:1, pp:51-62 [Journal]
  100. Peter Auer, Philip M. Long, Wolfgang Maass, Gerhard J. Woeginger
    On the Complexity of Function Learning. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1995, v:18, n:2-3, pp:187-230 [Journal]
  101. Zhixiang Chen, Wolfgang Maass
    On-Line Learning of Rectangles and Unions of Rectangles. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1994, v:17, n:2-3, pp:201-223 [Journal]
  102. Wolfgang Maass, György Turán
    Lower Bound Methods and Separation Results for On-Line Learning Models. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1992, v:9, n:, pp:107-145 [Journal]
  103. Wolfgang Maass, György Turán
    Algorithms and Lower Bounds for On-Line Learning of Geometrical Concepts. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1994, v:14, n:1, pp:251-269 [Journal]
  104. Prashant Joshi, Wolfgang Maass
    Movement Generation with Circuits of Spiking Neurons. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2005, v:17, n:8, pp:1715-1738 [Journal]
  105. Robert A. Legenstein, Christian Naeger, Wolfgang Maass
    What Can a Neuron Learn with Spike-Timing-Dependent Plasticity? [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2005, v:17, n:11, pp:2337-2382 [Journal]
  106. Wolfgang Maass
    On the Computational Power of Winner-Take-All. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2000, v:12, n:11, pp:2519-2535 [Journal]
  107. Wolfgang Maass
    Fast Sigmoidal Networks via Spiking Neurons. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 1997, v:9, n:2, pp:279-304 [Journal]
  108. Wolfgang Maass, Thomas Natschläger
    A Model for Fast Analog Computation Based on Unreliable Synapses. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2000, v:12, n:7, pp:1679-1704 [Journal]
  109. Wolfgang Maass, Thomas Natschläger, Henry Markram
    Real-Time Computing Without Stable States: A New Framework for Neural Computation Based on Perturbations. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2002, v:14, n:11, pp:2531-2560 [Journal]
  110. Wolfgang Maass, Pekka Orponen
    On the Effect of Analog Noise in Discrete-Time Analog Computations. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 1998, v:10, n:5, pp:1071-1095 [Journal]
  111. Wolfgang Maass, Eduardo D. Sontag
    Neural Systems as Nonlinear Filters. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2000, v:12, n:8, pp:1743-1772 [Journal]
  112. Wolfgang Maass, Eduardo D. Sontag
    Analog Neural Nets with Gaussian or Other Common Noise Distribution Cannot Recognize Arbitrary Regular Languages. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 1999, v:11, n:3, pp:771-782 [Journal]
  113. Wolfgang Maass, Anthony M. Zador
    Dynamic Stochastic Synapses as Computational Units. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 1999, v:11, n:4, pp:903-917 [Journal]
  114. Thomas Natschläger, Wolfgang Maass
    Computing the Optimally Fitted Spike Train for a Synapse. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2001, v:13, n:11, pp:2477-2494 [Journal]
  115. Kei Uchizawa, Rodney J. Douglas, Wolfgang Maass
    On the Computational Power of Threshold Circuits with Sparse Activity. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2006, v:18, n:12, pp:2994-3008 [Journal]
  116. Stephen Grossberg, Wolfgang Maass, Henry Markram
    Introduction: Spiking Neurons in Neuroscience and Technology. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2001, v:14, n:6-7, pp:587-0 [Journal]
  117. Wolfgang Maass
    Networks of spiking neurons: The third generation of neural network models. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 1997, v:10, n:9, pp:1659-1671 [Journal]
  118. Wolfgang Maass, Henry Markram
    Synapses as dynamic memory buffers. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2002, v:15, n:1, pp:155-161 [Journal]
  119. Thomas Natschläger, Wolfgang Maass
    Dynamics of information and emergent computation in generic neural microcircuit models. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2005, v:18, n:10, pp:1301-1308 [Journal]
  120. Alexander Kaske, Wolfgang Maass
    A model for the interaction of oscillations and pattern generation with real-time computing in generic neural microcircuit models. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2006, v:19, n:5, pp:600-609 [Journal]
  121. Wolfgang Maass
    "Imitation of life: how biology is inspiring computing" by Nancy Forbes. [Citation Graph (0, 0)][DBLP]
    Pattern Anal. Appl., 2006, v:8, n:4, pp:390-391 [Journal]
  122. Wolfgang Maass
    On the Complexity of Nonconvex Covering. [Citation Graph (0, 0)][DBLP]
    SIAM J. Comput., 1986, v:15, n:2, pp:453-467 [Journal]
  123. Wolfgang Maass
    Bounds for the Computational Power and Learning Complexity of Analog Neural Nets. [Citation Graph (0, 0)][DBLP]
    SIAM J. Comput., 1997, v:26, n:3, pp:708-732 [Journal]
  124. Wolfgang Maass, Amir Schorr
    Speed-Up of Turing Machines with One Work Tape and a Two-Way Input Tape. [Citation Graph (0, 0)][DBLP]
    SIAM J. Comput., 1987, v:16, n:1, pp:195-202 [Journal]
  125. Martin Dietzfelbinger, Wolfgang Maass
    The Complexity of Matrix Transposition on One-Tape Off-Line Turing Machines with Output Tape. [Citation Graph (0, 0)][DBLP]
    Theor. Comput. Sci., 1993, v:108, n:2, pp:271-290 [Journal]
  126. Martin Dietzfelbinger, Wolfgang Maass, Georg Schnitger
    The Complexity of Matrix Transposition on One-Tape Off-Line Turing Machines. [Citation Graph (0, 0)][DBLP]
    Theor. Comput. Sci., 1991, v:82, n:1, pp:113-129 [Journal]
  127. Steven Homer, Wolfgang Maass
    Oracle-Dependent Properties of the Lattice of NP Sets. [Citation Graph (0, 0)][DBLP]
    Theor. Comput. Sci., 1983, v:24, n:, pp:279-289 [Journal]
  128. Robert A. Legenstein, Wolfgang Maass
    Neural circuits for pattern recognition with small total wire length. [Citation Graph (0, 0)][DBLP]
    Theor. Comput. Sci., 2002, v:287, n:1, pp:239-249 [Journal]
  129. Wolfgang Maass
    On the relevance of time in neural computation and learning. [Citation Graph (0, 0)][DBLP]
    Theor. Comput. Sci., 2001, v:261, n:1, pp:157-178 [Journal]
  130. Thomas Natschläger, Wolfgang Maass
    Spiking neurons and the induction of finite state machines. [Citation Graph (0, 0)][DBLP]
    Theor. Comput. Sci., 2002, v:287, n:1, pp:251-265 [Journal]
  131. Wolfgang Maass
    Liquid Computing. [Citation Graph (0, 0)][DBLP]
    CiE, 2007, pp:507-516 [Conf]
  132. Gerhard Neumann, Michael Pfeiffer, Wolfgang Maass
    Efficient Continuous-Time Reinforcement Learning with Adaptive State Graphs. [Citation Graph (0, 0)][DBLP]
    ECML, 2007, pp:250-261 [Conf]
  133. Danko Nikolic, Stefan Haeusler, Wolf Singer, Wolfgang Maass
    Temporal dynamics of information content carried by neurons in the primary visual cortex. [Citation Graph (0, 0)][DBLP]
    NIPS, 2006, pp:1041-1048 [Conf]
  134. Stefan Klampfl, Robert A. Legenstein, Wolfgang Maass
    Information Bottleneck Optimization and Independent Component Extraction with Spiking Neurons. [Citation Graph (0, 0)][DBLP]
    NIPS, 2006, pp:713-720 [Conf]
  135. Robert A. Legenstein, Wolfgang Maass
    Edge of chaos and prediction of computational performance for neural circuit models. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2007, v:20, n:3, pp:323-334 [Journal]
  136. Herbert Jaeger, Wolfgang Maass, José Carlos Príncipe
    Special issue on echo state networks and liquid state machines. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2007, v:20, n:3, pp:287-289 [Journal]

  137. 08041 Abstracts Collection -- Recurrent Neural Networks - Models, Capacities, and Applications. [Citation Graph (, )][DBLP]


  138. 08041 Summary -- Recurrent Neural Networks - Models, Capacities, and Applications. [Citation Graph (, )][DBLP]


  139. Integration of Standardized and Non-Standardized Product Data. [Citation Graph (, )][DBLP]


  140. Learning complex motions by sequencing simpler motion templates. [Citation Graph (, )][DBLP]


  141. Theoretical Analysis of Learning with Reward-Modulated Spike-Timing-Dependent Plasticity. [Citation Graph (, )][DBLP]


  142. Simplified Rules and Theoretical Analysis for Information Bottleneck Optimization and PCA with Spiking Neurons. [Citation Graph (, )][DBLP]


  143. Hebbian Learning of Bayes Optimal Decisions. [Citation Graph (, )][DBLP]


  144. Vocabulary Patterns in Free-for-all Collaborative Indexing Systems. [Citation Graph (, )][DBLP]


  145. Ontology-Based Natural Language Processing for In-store Shopping Situations. [Citation Graph (, )][DBLP]


  146. Product-Centered Mobile Reasoning Support for Physical Shopping Situations. [Citation Graph (, )][DBLP]


  147. A Methodology for Content-Centered Design of Ambient Environments. [Citation Graph (, )][DBLP]


  148. Computational aspects of feedback in neural circuits. [Citation Graph (, )][DBLP]


  149. Energy Complexity and Entropy of Threshold Circuits. [Citation Graph (, )][DBLP]


  150. Adoption and Diffusion in Electronic Markets: An Empirical Analysis of Attributes Influencing the Adoption of Paid Content. [Citation Graph (, )][DBLP]


  151. Preface to the Focus Theme Section: 'Smart Products'. [Citation Graph (, )][DBLP]


Search in 0.784secs, Finished in 0.792secs
NOTICE1
System may not be available sometimes or not working properly, since it is still in development with continuous upgrades
NOTICE2
The rankings that are presented on this page should NOT be considered as formal since the citation info is incomplete in DBLP
 
Introduction Collection Based Clustering Ranking Paper Based Journals Conferences DB Status Statistics Search
System created by asidirop@csd.auth.gr [http://users.auth.gr/~asidirop/] © 2002
for Data Engineering Laboratory, Department of Informatics, Aristotle University © 2002