Peter Földiák publications

email: Peter.Foldiak (at) gmail (dot) com

Researcher ID: I-4987-2012

ORCID ID: 0000-0001-7407-5804

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P. Földiák, Object-oriented programming (in Hungarian), M.Sc. thesis, Faculty of Electrical Engineering, Technical University of Budapest, 1987.

H. G. E. Hentschel, H. B. Barlow, P. Foldiak, Path planning by a mobile vehicle using VLSI design automation algorithms. In Esprit Project P940, Depth and Motion Analysis. Report R.4.3.1., Motion Planning and Tracking, 1989.

H. B. Barlow, P. Földiák, "Adaptation and decorrelation in the cortex", in The Computing Neuron, ed. by C. Miall, R.M. Durbin, G.J. Mitchison, Addison-Wesley, Wokingham, England ISBN 020118348X ISBN-13: 978-0201183481, pp. 54-72, 1989. pdf or pdf

P. Földiák, Adaptive network for optimal linear feature extraction, Proceedings of the IEEE/INNS International Joint Conference on Neural Networks, Washington DC., June 18-22, vol. 1, pp. 401-405 (IEEE Press, New York, 1989). DOI:10.1109/IJCNN.1989.118615 or pdf

P. Földiák, Understanding simple unsupervised learning, Neural Network Review, Vol. 3, No. 2, pp 60-61, 1989.

P. Földiák, Forming sparse representations by local anti-Hebbian learning, Biological Cybernetics, vol. 64, pp. 165-170, 1990. DOI 10.1007/BF02331346 or pdf

P. Földiák, Models of sensory coding, Ph.D. dissertation, University of Cambridge, 1991. (reprinted as Technical Report No. CUED/F-INFENG/TR 91, Department of Engineering, University of Cambridge, 1992.) pdf or pdf

P. Földiák, Unsupervised feature learning, Proceedings of the CPI Neural Network Summer School, 15-19 April, 1991.

P. Földiák, Learning invariance from transformation sequences, Neural Computation, vol. 3, pp. 194-200, 1991. DOI 10.1162/neco.1991.3.2.194 or pdf (also reprinted in UnsupervisedLearning: Foundations of Neural Computation, eds. T.J. Sejnowski,G.E. Hinton, MIT Press, pp 63-69, 1998.)

P. Földiák, Principal component analysis in vowel recognition, Neural Network Review, 1992. pdf

P. Földiák, Statistical inference from neural population responses, poster at SERC III Workshop: Single cell recording and vision, Newcastle, January 1993.

P. Földiák, review of `Carpenter & Grossberg: Neural Networks for Vision and Image Processing' Network: Computation in Neural Systems, 4 (3): 411-412, 1993. pdf

P. Földiák, The 'Ideal Homunculus': statistical inference from neural population responses, in 'Computation and Neural Systems', eds. F. Eeckman and J. Bower, Kluwer Academic Publishers, Norwell, MA , pp 55-60, 1993. pdf

G. Wallis, E. T. Rolls, P. Földiák, Learning invariant responses to the natural transformations of objets, Proceedings of the International Joint Conference on Neural Networks, Nagoya, Japan, vol. 2, pp. 1087-1090, ISBN: 0-7803-1421-2, 1993. DOI: 10.1109/IJCNN.1993.716702 or pdf

P. Földiák, The 'ideal homunculus': Decoding neural population responses by Bayesian inference, Perception, vol. 22 (suppl.), 43, 1993. pdf

P. Földiák, M Young, Sparse coding in the primate cortex, in The Handbook of Brain Theory and Neural Networks (1st edition), ed. Michael A. Arbib, pp. 895-898, 1995. pdf

M. Oram, P. Földiák, Learning generalisation and localisation: Competing for stimulus type and receptive field, Neurocomputing, vol. 11, issue 2-4, pp. 297-321, 1996. DOI 10.1016/0925-2312(95)00099-2 or pdf

P. Földiák, Learning constancies for object perception, in Perceptual Constancy: Why things look as they do, eds. V Walsh & J J Kulikowski, Cambridge, U.K.: Cambridge Univ. Press , pp. 144-172, 1998. pdf

P. Földiák, What is wrong with prototypes, commentary, Behavioral and Brain Sciences, 21 (4) 471-472, 1998. pdf Linkto Abstract & to full target article

M.W. Oram, P. Földiák, D.I. Perrett, F. Sengpiel, The 'Ideal Homunculus': Decoding neural population signals, Trends in Neurosciences, 21, 259-265, 1998. DOI 10.1016/S0166-2236(97)01216-2 or pdf

D. Endres, P Földiák, Quadratic programming for learning sparse codes, In Proceedings of the Ninth International Conference on Artificial Neural Networks (ICANN99), IEE Conference Publication No. 470. London: Institution of Electrical Engineers, vol. 2, pp. 593-596, 1999. DOI 10.1049/cp:19991174 or pdf

Information Theory and the Brain, eds. R Baddeley, P Hancock, P Földiák, Cambridge University Press, 2000. ISBN 9780521631976, (2008 edition: ISBN 978-0521087865)

D. K. Xiao, R. Edwards, C. Keysers, P. Földiák, D. I. Perrett, T. Jellema, Searching for effective stimuli for cells in the temporal cortex. Soc. Neurosci. Abstr., Vol. 26, Part 1, p. 953, 2000.

R. Edwards, D. K. Xiao, P. Földiák, D. I. Perrett, T. Jenkins, Colour sensitivity of cells responsive to faces in the temporal cortex. Soc.Neurosci. Abstr., Vol. 26, Part 1, p. 953, 2000.

C. Keysers, D. K. Xiao, D. I. Perrett, P. Földiák, Minimal response duration for single cells in the macaque temporal cortex. Soc.Neurosci. Abstr., Vol. 26, Part 2, p. 1842, 2000.

C. Keysers, D. Xiao, P Földiák, D Perrett, The speed of sight, Journal of Cognitive Neuroscience, vol. 13, no. 1, pp 90-101, January 2001. DOI 10.1162/089892901564199 or pdf

P. Földiák, Stimulus optimization in primary visual cortex, Neurocomputing, 38-40 (1-4) 1217-1222, 2001. DOI 10.1016/S0925-2312(01)00570-7 or pdf (an unpublished version with a bit more detail is here).

D. Perrett, R. Edwards, D.K. Xiao, P Földiák, Binding of the colour and form of faces: Single cell and psychological studies, Journal of Cognitive Neuroscience B106 Suppl. S April 2002.

P. Földiák, Sparse coding in the primate cortex, in The Handbook of Brain Theory and Neural Networks, Second Edition, pp. 1064 - 1068, ed. Michael A. Arbib, MIT Press, 2002. pdf

P. Földiák, Decoding neural population activity, in Encyclopedia of Cognitive Science, ed. L. Nadel, Macmillan, Nature Publishing Group, 2002. ISBN 0470016191, DOI 10.1002/0470018860.s00346 or pdf

P. Földiák, Representation in neurons, in Encyclopedia of Cognitive Science, ed. L. Nadel, Macmillan, Nature Publishing Group, 2002. ISBN 0470016191, DOI 10.1002/0470018860.s00347 or pdf

R.Edwards, D. Xiao, C. Keysers, P. Földiák, D. Perrett, Colour sensitivity of cells responsive to complex stimuli in the temporal cortex, Journal of Neurophysiology, 90 (2) 1245 -1256, 2003. DOI 10.1152/jn.00524.2002 or pdf

P. Földiák, Sparse neural representation for semantic indexing, XIII Conference of the European Society of Cognitive Psychology (ESCOP-2003), Granada, Spain, poster. pdf

P. Földiák, D. K. Xiao, C. Keysers, R. Edwards and D. I. Perrett, Rapid serial visual presentation for the determination of neural selectivity in area STSa, Progress in Brain Research, 144: 107-116, 2004. DOI S0079-6123(03)14407-X or pdf (or see manuscript with clearer figures)

Foldiak, P., Soloviev, S., Vaina, L., Unsupervised learning of coordinate transformations using temporal coherence, Perception, 33 Suppl. 45, 2004. ECVP Abstract

C. Keysers, D.-K. Xiao, P Földiák, D.I. Perrett, Out of sight but not out of mind: The neurophysiology of iconic memory in the superior temporal sulcus, Cognitive Neuropsychology, 22 (3/4) 316-332, 2005. DOI 10.1080/02643290442000103 or pdf

D. Endres, P. Földiák, Bayesian bin distribution inference and mutual information, IEEE Transactions on Information Theory, 51 (11) 3766-3779, 2005. DOI 10.1109/TIT.2005.856954 or pdf

D. Endres, P. Földiák, Exact Bayesian bin classification: a fast alternative to Bayesian classification, Journal of Computational Neuroscience, 24(1) 21-35, 2008. DOI 10.1007/s10827-007-0039-5 or pdf

P Földiák, D M Endres; "Sparse coding"; Scholarpedia; 3(1):2984, 2008. DOI 10.4249/scholarpedia.2984

D M Endres, P Földiák, U Priss; "An application of formal concept analysis to neural decoding"; CLA 2008: the Sixth International Conference on Concept Lattices and Their Applications: Olomouc, Czech Republic, October 21-23, 2008; R Belohlavek, S O Kuznetsov (ed); Palacky University; pp 181-192, 2008. pdf

D M Endres, M W Oram, J.E. Schindelin, P Földiák; "Bayesian binning beats approximate alternatives: estimating peri-stimulus time histograms"; Advances in Neural Information Processing Systems 20; J.C. Platt, D. Koller, Y. Singer, S. Roweis (ed); MIT Press, Cambridge, Mass., USA; 393-400, 2008. pdf & supplements, pdf or pdf

Endres, Dominik, and Földiák, Peter: Interpreting the neural code with Formal Concept Analysis, Advances in Neural Information Processing Systems 21, 425–432, Eds: Koller, D., Schuurmans, D., Bengio, Y., and Bottou, L., MIT Press, Cambridge, MA, 2009. pdf & supplements or pdf

Földiák, P. Neural Coding: Non-Local but Explicit and Conceptual, Current Biology, 19 (19) R904-R906, 2009. DOI 10.1016/j.cub.2009.08.020 or pdf

D M Endres, P Földiák, U Priss; "An Application of Formal Concept Analysis to Semantic Neural Decoding"; Annals of Mathematics and Artificial Intelligence, 57(3-4):233–248, 2009. DOI 10.1007/s10472-010-9196-8 or pdf

D M Endres, J Schindelin, P Földiák, M W Oram, "Modelling spike trains and extracting response latency with Bayesian binning", Journal of Physiology (Paris), 104(3-4), pp 128-136, May-September 2010. DOI 10.1016/j.jphysparis.2009.11.015 or pdf

P Földiák, "Neural Control: Closed-Loop Human Brain Reading", Current Biology, 21(2) R80-R81, 2011. DOI 10.1016/j.cub.2010.12.023 or pdf

P Földiák, "Sparse and explicit neural coding", in Principles of Neural Coding, eds. R. Quian Quiroga, S. Panzeri, Chapter 19, pp 379-389, CRC Press, ISBN-10: 1439853304, ISBN-13: 978-1439853306, 2013. pdf.

Artur d’Avila Garcez, Tarek R. Besold, Luc de Raedt, Peter Földiak, Pascal Hitzler, Thomas Icard, Kai-Uwe Kühnberger, Luis C. Lamb, Risto Miikkulainen, Daniel L. Silver, "Neural-Symbolic Learning and Reasoning: Contributions and Challenges", Proceedings of the AAAI Spring Symposium on Knowledge Representation and Reasoning: Integrating Symbolic and Neural Approaches, Stanford, 2015. DOI 10.13140/2.1.1779.4243 pdf

G Berend, M Makrai, P Földiák, "300-sparsans at SemEval-2018 Task 9: Hypernymy as interaction of sparse attributes", in the Proceedings of The 12th International Workshop on Semantic Evaluation , pp 928–934, Association for Computational Linguistics, New Orleans2018. DOI 10.18653/v1/S18-1152 pdf