Ing. Jiří Grim, CSc.

senior research fellow

Jiří Grim
grim@utia.cas.cz 266052215
Department: Pattern Recognition Department
Research interests: Statistical Pattern Recognition, Probabilistic Neural Networks, Probabilistic Expert Systems, Application of Distribution Mixtures

Biography

Publication list

He graduated in physical electronics (M.S.-level) from the Czech Technical University, Prague. He received a Ph.D. degree in computer science
from the Czech Academy of Sciences in 1981. Currently he is with the Institute of Information Theory and Automation of the Czech Academy of Sciences, Prague. His research interests include statistical pattern recognition, application of distribution mixtures to image processing and the probabilistic approach to neural networks.

 

Statistical model of the 2001 Czech Census for Interactive Presentation 
 

Presentations: A Statistical Approach to Local Evaluation of a Single Texture Image: pdf
Distribution mixtures I: pdf
Distribution mixtures II: pdf

Paper Awards:
Best Publication Award (Internal Competition of the Institute): Grim J: Approximation of Unknown Multivariate Probability Distributions by Using Mixtures of Product Components: A Tutorial, International Journal of Pattern Recognition and Artificial Intelligence, Vol. 31, No. 9, 2017.

Best Publication Award (Internal Competition of the Institute): Grim J: Sequential Pattern Recognition by Maximum Conditional Informativity, Pattern Recognition Letters, Vol. 45, No. 1, pp. 39-45, 2014.

Award of the Academy of Sciences of the Czech Republic for scientific outcome: Mathematical modeling of visual properties of surface materials, member of the team led by prof. Ing. Michal Haindl, DrSc., 2011.

Best Publication Award (Internal Competition of the Institute): Somol P., Grim J., Novovičová J., Pudil P.: Improving feature selection process resistance to failures caused by curse-of-dimensionality effects, Kybernetika, 2011.

Best Paper Award: Grim Jiří, Somol Petr, Pudil Pavel: Digital Image Forgery Detection by Local Statistical Models, Proc. 2010 Sixth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, Darmstadt, 2010.

Best Publication Award (Internal Competition of the Institute): Grim J., Somol P., Haindl M., Daneš J: Computer-Aided Evaluation of Screening Mammograms Based on Local Texture Models. IEEE Transactions on Image Processing, 2009.

Best Publication Award (Internal Competition of the Institute): Grim J., Hora, J.: Iterative principles of recognition in probabilistic neural networks. Neural Networks. Special Issue, 2008.

Best Publication Award (Internal Competition of the Institute): Grim J.: Self-organizing maps and probabilistic neural networks. Neural Network World, 3(10): 407-415. 2000.

Springer Best Presentation Award: Grim J., Pudil P., Somol P.: Recognition of handwritten numerals by structural probabilistic neural network, Proc. Second ICSC Symposium on Neural Computation“, Berlin, 2000.

F. de P. Hanika Memorial Award: Grim J.: A Dialog Presentation of Census Results by Means of the Probabilistic Expert System PES, Proc. Eleventh European Meeting on Cybernetics and Systems Research“, Vienna, 1992.
 

Books and chapters

  1. Grim Jiří, Somol Petr: A Statistical Review of the MNIST Benchmark Data Problem, Advances in Pattern Recognition Research, p. 172-193, Eds: Lu T., Chao T.H. Download [2018]
  2. Vajda Igor, Grim Jiří: Neural networks, Systems Science and Cybernetics, p. 224-248 Download [2008]
  3. Grim Jiří: Pravděpodobnostní neuronové sítě, Umělá inteligence (4), p. 276-312, Eds: Mařík V., Štěpánková O., Lažanský J., Academia (Praha, 2003) [2003]
  4. Grim Jiří, Boček Pavel, Pudil Pavel: Interaktivní prezentace výsledků sčítání lidu pomocí pravděpodobnostních modelů se zaručenou ochranou anonymity dat, Manažerské rozhledy FM 2001. Sborník příspěvků, p. 13-18, VŠE (Jindřichův Hradec, 2002) [2002]

Journal articles

  1. Miklík Dalibor, Grim Jiří, Elleder Daniel, Hejnar Jiří: Unraveling the palindromic and nonpalindromic motifs of retroviral integration site sequences by statistical mixture models, Genome Research 33 8 (2023), p. 1395-1408 Download DOI: 10.1101/gr.277694.123 [2023]
  2. Grim Jiří: Approximation of Unknown Multivariate Probability Distributions by Using Mixtures of Product Components: A Tutorial, International Journal of Pattern Recognition and Artificial Intelligence 31 Download DOI: 10.1142/S0218001417500288 [2017]
  3. Grim Jiří: Sequential pattern recognition by maximum conditional informativity, Pattern Recognition Letters 45 1 (2014), p. 39-45 Download DOI: 10.1016/j.patrec.2014.02.024 [2014]
  4. Somol Petr, Grim Jiří, Novovičová Jana, Pudil P.: Improving feature selection process resistance to failures caused by curse-of-dimensionality effects, Kybernetika 47 3 (2011), p. 401-425 Download [2011]
  5. Haindl Michal, Havlíček Vojtěch, Grim Jiří: Probabilistic mixture-based image modelling, Kybernetika 47 3 (2011), p. 482-500 Download [2011]
  6. Grim Jiří, Hora Jan, Boček Pavel, Somol Petr, Pudil Pavel: Statistical Model of the 2001 Czech Census for Interactive Presentation, Journal of Official Statistics 4 (2010), p. 1-23 Download [2010]
  7. Grim Jiří, Hora J., Somol Petr, Boček Pavel, Pudil P.: Interaktivní statistický model dat ze sčítání lidu v České republice v r. 2001, Statistika: Statistics and Economy Journal 89 4 (2009), p. 285-299 Download [2009]
  8. Grim Jiří, Somol Petr, Haindl Michal, Daneš J.: Computer-Aided Evaluation of Screening Mammograms Based on Local Texture Models, IEEE Transactions on Image Processing 18 4 (2009), p. 765-773 DOI: 10.1109/TIP.2008.2011168 [2009]
  9. Haindl Michal, Havlíček Vojtěch, Grim Jiří: Probabilistic Discrete Mixtures Colour Texture Models, Lecture Notes in Computer Science 2008 5197 (2008), p. 675-682 Download DOI: dx.doi.org/10.1007/978-3-540-85920-8_82 [2008]
  10. Grim Jiří, Hora Jan: Iterative principles of recognition in probabilistic neural networks, Neural Networks 21 6 (2008), p. 838-846 DOI: 10.1016/j.neunet.2008.03.002 [2008]
  11. Grim Jiří: Neuromorphic features of probabilistic neural networks, Kybernetika 43 5 (2007), p. 697-712 [2007]
  12. Grim Jiří, Hora Jan: Minimum Information Loss Cluster Analysis for Cathegorical Data, Lecture Notes in Computer Science 2007, p. 233-247 [2007]
  13. Haindl Michal, Grim Jiří, Mikeš Stanislav: Texture Defect Detection, Lecture Notes in Computer Science 2007, p. 987-994 Download [2007]
  14. Grim Jiří, Somol Petr, Haindl Michal, Pudil Pavel: Color Texture Segmentation by Decomposition of Gaussian Mixture Model, Lecture Notes in Computer Science 19 4225 (2006), p. 287-296 Download [2006]
  15. Grim Jiří: EM cluster analysis for categorical data, Lecture Notes in Computer Science 44 4109 (2006), p. 640-648 [2006]
  16. Grim Jiří, Somol Petr, Pudil Pavel: Probabilistic neural network playing and learning Tic-Tac-Toe, Pattern Recognition Letters 26 12 (2005), p. 1866-1873 [2005]
  17. Grim Jiří, Hora J., Pudil Pavel: Interaktivní reprodukce výsledků sčítání lidu pomocí statistického modelu se zaručenou ochranou anonymity dat, Statistika: Statistics and Economy Journal 40 5 (2004), p. 400-414 [2004]
  18. Grim Jiří, Just P., Pudil Pavel: Strictly modular probabilistic neural networks for pattern recognition, Neural Network World 13 6 (2003), p. 599-615 [2003]
  19. Grim Jiří, Haindl Michal: Texture modelling by discrete distribution mixtures, Computational Statistics and Data Analysis 41, p. 603-615 [2003]
  20. Grim Jiří, Kittler J., Pudil Pavel, Somol Petr: Multiple classifier fusion in probabilistic neural networks, Pattern Analysis and Applications 5 7 (2002), p. 221-233 [2002]
  21. Grim Jiří, Pudil Pavel, Somol Petr: Probabilistic information retrieval from census data based on distribution mixtures, Acta Oeconomica Pragensia 8 2 (2000), p. 41-47 [2000]
  22. Grim Jiří: Self-organizing maps and probabilistic neural networks, Neural Network World 10 3 (2000), p. 407-415 [2000]
  23. Grim Jiří, Vejvalková J.: An iterative inference mechanism for the probabilistic expert system PES, International Journal of General Systems 27, p. 373-396 [1999]
  24. Grim Jiří: Mixture of experts architectures for neural networks as a special case of conditional expectation formula, Kybernetika 34 4 (1998), p. 417-422 [1998]
  25. Vajda Igor, Grim Jiří: About the maximum information and maximum likelihood principles in neural networks, Kybernetika 34 4 (1998), p. 485-494 [1998]
  26. Grim Jiří: Knowledge representation and uncertainty processing in the probabilistic expert system PES, International Journal of General Systems 22 2 (1994), p. 103-111 [1994]
  27. Grim Jiří, Kolář Pavel: Akciové společnosti s téměř jistým převisem poptávky ve 4. kole, Hospodářské noviny 209 (1992), p. 8 [1992]
  28. Boček Pavel, Grim Jiří, Kolář Pavel: Kupónová privatizace zdárně pokračuje, Akcionář 3 15 (1992), p. 8 [1992]
  29. Boček Pavel, Grim Jiří, Kolář Pavel: Podle počítače. Porovnání výkonnosti českých a slovenských podniků, zařazených do první vlny kupónové privatizace, Hospodářské noviny 115 (1992), p. 8 [1992]
  30. Boček Pavel, Grim Jiří, Kolář Pavel: Kam s kupóny v druhém kole?, Hospodářské noviny 135 (1992), p. 8 [1992]
  31. Grim Jiří, Kolář Pavel: Kuponová privatizace: odhadování rizika převisů, Akcionář 3 21 (1992), p. 10-11 [1992]
  32. Grim Jiří: Probabilistic expert systems and distribution mixtures, Computers and Artificial Intelligence 9 3 (1990), p. 241-256 [1990]

Other publications

  1. Grim Jiří: Unsupervised Verification of Fake News by Public Opinion, UTIA (Praha, 2021) Download [2021]
  2. Grim Jiří: Platební regulační mechanismus jako zdroj zvyšování platů ve zdravotnictví, ÚTIA AV ČR v.v.i (Praha, 2018) Download [2018]
  3. Grim Jiří: Vyhodnocování grantové soutěže pomocí otevřené expertní databáze, ÚTIA AV ČR v.v.i (Praha, 2018) Download [2018]
  4. Grim Jiří: Feasibility Study of an Interactive Medical Diagnostic Wikipedia, SPMS 2016 Stochastic and Physical Monitoring Systems, p. 31-45 Download [2016]
  5. Grim Jiří, Pudil P.: Mixtures of Product Components versus Mixtures of Dependence Trees, Computational Intelligence, p. 365-382 Download DOI: 10.1007/978-3-319-26393-9_22 [2016]
  6. Grim Jiří: Approximating Probability Densities by Mixtures of Gaussian Dependence Trees, Stochastic and Physical Monitoring Systems, SPMS 2014 Download [2014]
  7. Grim Jiří, Pudil P.: Pattern Recognition by Probabilistic Neural Networks - Mixtures of Product Components versus Mixtures of Dependence Trees, NCTA2014 - International Conference on Neural Computation Theory and Applications, p. 65-75 Download [2014]
  8. Filip Jiří, Grim Jiří, Haindl Michal: A Probabilistic Approach to Rough Texture Compression and Rendering, MUSCLE International Workshop on Computational Intelligence for Multimedia Understanding, p. 8-12 Download [2013]
  9. Somol Petr, Grim Jiří, Filip Jiří, Pudil P.: On Stopping Rules in Dependency-Aware Feature Ranking, Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, p. 286-293 Download DOI: 10.1007/978-3-642-41822-8_36 [2013]
  10. Pudil P., Blažek L., Částek O., Somol P., Grim Jiří: Identification of Corporate Competitiveness Factors – Comparing Different Approaches, Proceedings of the International Conference on Management, Leadership and Governance 2013, p. 259-267 Download [2013]
  11. Grim Jiří, Lee G. L.: Evaluation of Screening Mammograms by Local Structural Mixture Models, Stochastic and Physical Monitoring Systems SPSM 2012, p. 51-61 Download [2012]
  12. Grim Jiří: Preprocessing of Screening Mammograms Based on Local Statistical Models, Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies, ISABEL 2011, p. 1-5 Download [2011]
  13. Somol Petr, Grim Jiří, Pudil P.: Fast Dependency-Aware Feature Selection in Very-High-Dimensional Pattern Recognition, Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC 2011), p. 502-509 Download DOI: 10.1109/ICSMC.2011.6083733 [2011]
  14. Somol Petr, Grim Jiří: Fast Dependency-Aware Feature Selection in Very-High-Dimensional Pattern Recognition Problems, ÚTIA AV ČR, v.v.i (Praha, 2011) Download [2011]
  15. Grim Jiří, Hora Jan: Computational Properties of Probabilistic Neural Networks, Artificial Neural Networks – ICANN 2010, p. 31-40, Eds: Diamantaras K., Duch Wlodzislaw, Iliadis L.S. Download DOI: 10.1007/978-3-642-15825-4_4 [2010]
  16. Somol Petr, Grim Jiří, Pudil Pavel: The Problem of Fragile Feature Subset Preference in Feature Selection Methods and A Proposal of Algorithmic Workaround, Proc. 2010 Int. Conf. on Pattern Recognition, p. 4396-4399 Download [2010]
  17. Grim Jiří, Somol Petr, Pudil Pavel: Digital Image Forgery Detection by Local Statistical Models, 2010 Sixth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, p. 579-582, Eds: Echizen Isao, Pan Jeng-Shyang, Fellner Dieter, Nouak Alexander, Kuijper Arjan, Jain Lakhmi C. Download DOI: 10.1109/IIHMSP.2010.147 [2010]
  18. Haindl Michal, Havlíček Vojtěch, Grim Jiří: Colour Texture Representation Based on Multivariate Bernoulli Mixtures, 10th International Conference on Information Sciences, Signal Processing and their Applications, p. 578-581 Download [2010]
  19. Grim Jiří, Hora Jan: Recognition of Properties by Probabilistic Neural Networks, Artificial Neural Networks - ICANN 2009, p. 165-174, Eds: Polycarpou Marios, Alipi Cesare, Panayiotou Christos, Ellinas Georgios Download [2009]
  20. Somol Petr, Grim Jiří, Pudil Pavel: Criteria Ensembles in Feature Selection, Multiple Classifier Systems, LNCS 5519, p. 304-313, Eds: Benediktsson J.A., Kittler J., Roli F. [2009]
  21. Grim Jiří, Novovičová Jana, Somol Petr: Structural Poisson Mixtures for Classification of Documents, Proceedings of the 19th International Conference on Pattern Recognition, p. 1324-1327 Download [2008]
  22. Somol Petr, Novovičová Jana, Grim Jiří, Pudil Pavel: Dynamic Oscillating Search Algorithm for Feature Selection, ICPR 2008 Proceedings (Int. Conf. on Pattern Recognition), p. 2308-2311 Download [2008]
  23. Grim Jiří, Somol Petr, Pudil Pavel, Míková I., Malec M.: Texture Oriented Image Inpainting based on Local Statistical Model, Proc. 10th IASTED Conf. on Signal & Image Processing, SIP 2008, p. 15-20 Download [2008]
  24. Grim Jiří: Extraction of Binary Features by Probabilistic Neural Networks, Artificial Neural Networks - ICANN 2008, p. 52-61, Eds: Kůrková V., Neruda R., Koutník J. [2008]
  25. Grim Jiří, Somol Petr: Diagnostic Enhancement of Screening Mammograms by Means of Local Texture Models, ÚTIA AV ČR (Praha, 2008) [2008]
  26. Grim Jiří, Hora Jan: Recurrent Bayesian Reasoning in Probabilistic Neural Networks, Artificial Neural Networks - ICANN 2007, p. 129-138, Eds: Marques de Sá J., Alexandre L. A., Duch W., Mandic D. [2007]
  27. Grim Jiří: Neuromorphic Features of Probabilistic Neural Networks, ÚTIA AV ČR (Praha, 2006) [2006]
  28. Grim Jiří, Haindl Michal, Somol Petr, Pudil Pavel: A subspace approach to texture modelling by using Gaussian mixtures, Proceedings of the 18th Conference on Pattern Recognition. ICPR 2006, p. 235-238, Eds: Haralic B., Ho T. K. [2006]
  29. Haindl Michal, Grim Jiří, Pudil Pavel, Kudo M.: A hybrid BTF model based on Gaussian mixtures, Texture 2005. Proceedings of the 4th International Workshop on Texture Analysis, p. 95-100, Eds: Chantler M., Drbohlav O., IEEE (Los Alamitos, 2005) [2005]
  30. Grim Jiří, Somol Petr, Haindl Michal, Pudil Pavel: A statistical approach to local evalution of a single texture image, Proceedings of the Sixtheenth Annual Symposium of the Pattern Recognition Association of South Africa, p. 171-176 [2005]
  31. Grim Jiří, Hora J., Boček Pavel, Somol Petr, Pudil P.: Information analysis of census data by using statistical models, Proceedings of the International Conference on Statistics - Investment in the Future, p. 1-7 [2004]
  32. Somol Petr, Pudil Pavel, Grim Jiří: On prediction mechanisms in Fast Branch & Bound algorithms, Structural, Syntactic, and Statistical Pattern Recognition. Joint IAPR International Workshops SSPR 2004 and SPR 2004. Proceedings, p. 716-724 Download [2004]
  33. Haindl Michal, Grim Jiří, Somol Petr, Pudil Pavel, Kudo M.: A Gaussian mixture-based colour texture model, Proceedings of the 17th IAPR International Conference on Pattern Recognition, p. 177-180 [2004]
  34. Grim Jiří, Somol Petr, Pudil Pavel, Just P.: Probabilistic neural network playing a simple game, Artificial Neural Networks in Pattern Recognition. Proceedings, p. 132-138, Eds: Marinai S., Gori M., University of Florence (Florence, 2003) [2003]
  35. Grim Jiří, Pudil Pavel, Somol Petr: Boosting in probabilistic neural networks, Proceedings of the 16th International Conference on Pattern Recognition, p. 136-139, Eds: Kasturi R., Laurendeau D., Suen C., IEEE Computer Society (Los Alamitos, 2002) Download [2002]
  36. Grim Jiří, Haindl Michal: A discrete mixtures colour texture model, Texture 2002. The 2nd International Workshop on Texture Analysis and Synthesis, p. 59-62, HeriotWatt University (Glasgow, 2002) [2002]
  37. Somol Petr, Pudil Pavel, Grim Jiří: Branch & Bound algorithm with partial prediction for use with recursive and non-recursive criterion forms, Advances in Pattern Recognition - ICAPR 2001. Proceedings, p. 425-434, Eds: Singh S., Murshed N., Kropatsch W., Springer (Heidelberg, 2001) Download [2001]
  38. Grim Jiří, Haindl Michal: A Monospectral Probabilistic Discrete Mixture Texture Model, ÚTIA AV ČR (Praha, 2001) [2001]
  39. Grim Jiří: Latent Structure Analysis for Categorical Data, ÚTIA AV ČR (Praha, 2001) [2001]
  40. Grim Jiří, Haindl Michal: A mixture-based colour texture model. Abstract, Recent Developments in Mixture Modelling. Abstracts, p. 58, Eds: Bohning D., Seidel W., Universität der Bundeswehr (Hamburg, 2001) [2001]
  41. Grim Jiří: The models of conditional independence: Finite mixtures of product components and their application. Abstract, Recent Developments in Mixture Modelling. Abstracts, p. 59, Eds: Boehning D., Seidel W., Universität der Bundeswehr (Hamburg, 2001) [2001]
  42. Grim Jiří, Boček Pavel, Pudil Pavel: Safe dissemination of census results by means of interactive probabilistic models, Proceedings of the ETK-NTTS 2001 Conference, p. 849-856, Eds: Nanopoulos P., Wilkinson D., European Communities (Rome, 2001) [2001]
  43. Grim Jiří, Kittler J., Pudil Pavel, Somol Petr: Information analysis of multiple classifier fusion, Multiple Classifier Systems, p. 168-177, Eds: Kittler J., Roli F., Springer (Berlin, 2001) [2001]
  44. Grim Jiří, Pudil Pavel, Somol Petr: Multivariate structural Bernoulli mixtures for recognition of handwritten numerals, Proceedings of the 15th International Conference on Pattern Recognition, p. 585-589, Eds: Sanfeliu A., Villanueva J. J., Vanrell M., IEEE Computer Society (Los Alamitos, 2000) [2000]
  45. Grim Jiří, Kittler J., Pudil Pavel, Somol Petr: Combining multiple classifiers in probabilistic neural networks, Multiple Classifier Systems, p. 157-166, Eds: Kittler J., Roli F., Springer (Berlin, 2000) [2000]
  46. Grim Jiří, Pudil Pavel, Somol Petr: Recognition of handwritten numerals by structural probabilistic neural networks, Proceedings of the Second ICSC Symposium on Neural Computation, p. 528-534, Eds: Bothe H., Rojas R., ICSC (Wetaskiwin, 2000) Download [2000]
  47. Grim Jiří, Pudil Pavel: Interactive presentation of socio-economic databases by means of probabilistic models, Proceedings of the 17th International Conference on Mathematical Methods in Economics '99, p. 103-108, VŠE (Praha, 1999) [1999]
  48. Grim Jiří: Information approach to structural optimization of probabilistic neural networks, Fourth European Congress on Systems Science, p. 527-539, Eds: Ferrer L., Caselles A., SESGE (Valencia, 1999) [1999]
  49. Grim Jiří: A sequential modification of EM algorithm, Classification in the Information Age. Proceedings, p. 163-170, Eds: Gaul W., Locarek-Junge H., Springer (Berlin, 1999) Download [1999]
  50. Grim Jiří: Pravděpodobnostní neuronové sítě, ÚTIA AV ČR (Praha, 1999) [1999]
  51. Grim Jiří, Pudil Pavel: On virtually binary nature of probabilistic neural networks, Advances in Pattern Recognition. Proceedings, p. 765-774, Eds: Amin A., Dori D., Pudil P., Freeman H., Springer (Berlin, 1998) [1998]
  52. Grim Jiří: Discretization of probabilistic neural networks with bounded information loss, Preprints of the 3rd European IEEE Workshop on Computer-Intensive Methods in Control and Data Processing, p. 205-210, Eds: Rojíček J., Valečková M., Kárný M., Warwick K., ÚTIA AV ČR (Praha, 1998) Download [1998]
  53. Grim Jiří, Novovičová Jana, Pudil Pavel, Somol Petr, Ferri F. J.: Initializing normal mixtures of densities, Proceedings of the 14th International Conference on Pattern Recognition, p. 886-890, Eds: Jain A. K., Venkatesh S., Lovell B. C., IEEE (Los Alamitos, 1998) [1998]
  54. Pudil Pavel, Novovičová Jana, Grim Jiří: Proceedings of the 1st IAPR TC1 Workshop on Statistical Techniques in Pattern Recognition, ÚTIA AV ČR (Praha, 1997) [1997]
  55. Vajda Igor, Grim Jiří: About the maximum information and maximum likelihood principles in neural networks, Proceedings of the 1st IAPR TC1 Workshop on Statistical Techniques in Pattern Recognition, p. 189-197, Eds: Pudil P., Novovičová J., Grim J., ÚTIA AV ČR (Praha, 1997) [1997]
  56. Grim Jiří: Mixture of experts architectures for neural networks as a special case of conditional expectation formula, Proceedings of the 1st IAPR TC1 Workshop on Statistical Techniques in Pattern Recognition, p. 55-60, Eds: Pudil P., Novovičová J., Grim J., ÚTIA AV ČR (Praha, 1997) Download [1997]
  57. Grim Jiří: Maximum-Likelihood Structuring of Probabilistic Neural Networks, ÚTIA AV ČR (Praha, 1997) Download [1997]
  58. Vajda Igor, Grim Jiří: About Optimality of Probabilistic Basic Function Neural Networks, ÚTIA AV ČR (Praha, 1996) [1996]
  59. Grim Jiří: An Alternative Design of Mixture of Experts Architectures for Neural Networks, ÚTIA AV ČR (Praha, 1996) [1996]
  60. Grim Jiří: Design of multilayer neural networks by information preserving transforms, Third European Congress on Systems Science, p. 977-982, Eds: Pessa E., Penna M. P., Montesanto A., Edizioni Kappa (Roma, 1996) Download [1996]
  61. Grim Jiří: Discretization in Probabilistic Neural Networks with Bounded Information Loss, ÚTIA AV ČR (Praha, 1996) [1996]
  62. Grim Jiří: Maximum-likelihood design of layered neural networks, International Conference on Pattern Recognition. Proceedings, p. 85-89, IEEE Computer Society Press (Los Alamitos, 1996) [1996]
  63. Grim Jiří, Vavruška D.: Probabilistic Knowledge-based Models Defined by Finite Distribution Mixtures, ÚTIA AV ČR (Praha, 1996) [1996]
  64. Grim Jiří, Boček Pavel: Statistical model of Prague households for interactive presentation of census data, SoftStat '95. Advances in Statistical Software 5, p. 271-278, Eds: Faulbaum F., Bandilla W., Lucius & Lucius (Stuttgart, 1996) [1996]
  65. Grim Jiří, Vejvalková J.: An Interative Inference Mechanism for the Probabilistic Expert System PES, ÚTIA AV ČR (Praha, 1996) [1996]
  66. Vajda Igor, Grim Jiří: On Information Theoretic Optimality of Radial Basis Function Neural Networks, ÚTIA AV ČR (Praha, 1996) [1996]
  67. Grim Jiří: Multidimensional problems in the probabilistic expert system PES, Computer-Intensive Methods in Control and Signal Processing, p. 83-90, Eds: Kulhavá L., Kárný M., Warwick K., ÚTIA AV ČR (Praha, 1994) [1994]
  68. Grim Jiří, Boček Pavel: Statistical Model of Prague Households for Interactive Presentation of Census Data, ÚTIA AV ČR (Praha, 1994) [1994]
  69. Grim Jiří: Individualized voting scheme - a democratic violation of the democratic voting principle, Cybernetics and Systems '94, p. 1081-1088, World Scientific (Singapore, 1994) [1994]
  70. Grim Jiří: A Dialog Presentation of Census Results by Means of the Probabilistic Expert System PES, 11th European Meeting on Cybernetics and Systems Research '92, p. 997-1004, World Scientific (Singapore, 1992) [1992]
  71. Grim Jiří: Knowledge Representation and Uncertainty Processing in the Probabilistic Expert System PES, Workshop on Uncertainty Processing in Expert Systems, p. -, ÚTIA ČSAV (Prague, 1991) [1991]
  72. Grim Jiří: Histogramový expertní systém, MEDSOFT 88 - seminář o medicínském software, p. 28-30, ČSVTS Fakulta všeobecného lékařství UK (Praha, 1988) [1988]
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