Understanding neural networks through visualization

Neurodynamics, time-dependent:

1. Dobosz K, Duch W, Visualization for Understanding of Neurodynamical Systems.
   Cognitive Neurodynamics 5(2), 145-160, 2011.
2. Duch W, Neurodynamics and the mind.
   Proc. of the International Joint Conference on Neural Networks, San Jose, CA, IEEE Press, pp. 3227--3234, 2011.
   Presented at the IJCNN 2011, San Jose, special session "What Neural Modeling Tells Us about Ourselves''.
3. Duch W, Dobosz K, Attractors in Neurodynamical Systems.
   Advances in Cognitive Neurodynamics II (eds. R. Wang, F. Gu), pp. 157-161, 2011
4. Dobosz K, Duch W. (2010) Understanding Neurodynamical Systems via Fuzzy Symbolic Dynamics.
   Neural Networks Vol. 23 (2010) 487-496, 2010
   http://dx.doi.org/10.1016/j.neunet.2009.12.005
5. Duch W, Dobosz K, Jovanovic A, Klonowski W. (2010) Exploring the landscape of brain states
   NeuroMath COST Action BM0601, archived in Frontiers in Neuroscience.

6. Dobosz K, Duch W, Fuzzy Symbolic Dynamics for Global Visualization.
   Lecture Notes in Computer Science, vol. 5164, 471-478, 2008.
   Presented at: International Conference on Artificial Neural Networks (ICANN'08), Prague, Czech Republic
7. Dobosz K, Duch W, Global Visualization of Neural Dynamics.
   Neuromath Workshop, Dornburg Castle, Jena, Germany, 28-29 April 2008, pp. 15-16

Feedforward networks.

1. Duch, W, Coloring black boxes: visualization of neural network decisions.
   International Joint Conference on Neural Networks, Portland, Oregon, 2003, IEEE Press, Vol. I, pp. 1735-1740
   Matlab files with software/data used in this paper, 1 MB. Please note that it requires the Netlab neural network toolbox to run.

2. Duch W, Visualization of hidden node activity in neural networks: I. Visualization methods.
   The 7th International Conference on Artificial Intelligence and Soft Computing (ICAISC), Zakopane, Poland, June 2004. Eds. L. Rutkowski, J. Siekemann, R. Tadeusiewicz, L. Zadeh. Lecture Notes in AI Vol. 3070 (2004) 38-43
3. Duch W, Visualization of hidden node activity in neural networks: II. Application to RBF networks.
   The 7th International Conference on Artificial Intelligence and Soft Computing (ICAISC), Zakopane, Poland, June 2004. Eds. L. Rutkowski, J. Siekemann, R. Tadeusiewicz, L. Zadeh. Lecture Notes in AI Vol. 3070 (2004) 44-49
4. Kordos M, Duch W, A Survey of Factors Influencing MLP Error Surface.
   Control and Cybernetics 33(4) (2004) 611-631.
5. Kordos M, Duch W, On Some Factors Influencing MLP Error Surface.
   The 7th International Conference on Artificial Intelligence and Soft Computing (ICAISC), Zakopane, Poland, June 2004. Eds. L. Rutkowski, J. Siekemann, R. Tadeusiewicz, L. Zadeh. Lecture Notes in AI Vol. 3070 (2004) 217-222
6. Duch W, Internal representations of multi-layered perceptrons.
   In: Issues in Intelligent Systems: Paradigms. Eds. O. Hryniewicz, J. Kacprzyk, J. Koronacki, S.T. Wierzchoń, Exit, Warsaw, Poland (2005), pp. 49-62.
7. F. Piękniewski and L. Rybicki: Visual comparison of performance for different activation functions in MLP networks, IJCNN 2004.

8. F. Piękniewski and L. Rybicki: Visualizing and Analyzing Multidimensional Output from MLP Networks via Barycentric Projections, ICAISC 2004.

Also connected with visualization:

• Duch W, Matykiewicz, P. Minimum Spanning Trees Displaying Semantic Similarity.
  Intelligent Information Processing and Web Mining, Advances in Soft Computing, Springer Verlag, ISBN 3-540-25056-5 (Eds. Klopotek, M.A., Wierzchon, S.T., Trojanowski, K.), pp. 31-40, 2005.
• Naud A, Duch W, Visualization of large data sets using MDS combined with LVQ. In: Neural Networks and Soft Computing (eds. L. Rutkowski and J. Kacprzyk), Advances in Soft Computing, Physica Verlag (Springer), pp. 632-637, 2002.
• Duch Włodzisław, Rafał Adamczak, Norbert Jankowski, Antoine Naud, Jerzy Gomuła, Tomasz Kucharski (1996) Neural-based classification and visualization methods with applications to psychometry.
  34th International Seminar on Statistics and Clinical Practice, Warsaw 24-28.06.1996 (extended abstract), pp. 93-94
• Naud A and Duch W, Interactive data exploration using MDS mapping.
  5th Conference on Neural Networks and Soft Computing, Zakopane, June 2000, pp. 255-260
• Duch W and Naud A (1996) Simplexes, Multi-Dimensional Scaling and Self-Organized Mapping
  Proc. of the 8th joint EPS-APS International Conference on Physics Computing '96, Kraków 17-21.9.1996, pp. 367-370
• Duch W and Naud A (1996) On global self-organizing maps
  Proc. of the European Symposium on Artificial Neural Networks (ESANN'96), Bruge 22-26.4.1996, pp. 91-96
• Duch W and Naud A (1996) Multidimensional scaling and Kohonen's self-organizing maps .
  Proceedings of the Second Conference on Neural Networks and their applications, Orle Gniazdo, 30.IV-4.V.1996, pp. 138-143