Information theory and statistics

A new look at the statistical model identification

Akaike, H. (1974) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1974.1100705 · Cited by 51,879

Multiresolution gray-scale and rotation invariant texture classification with local binary patterns

Ojala, T., Pietikainen, M., & Maenpaa, T. (2002) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2002.1017623 · Cited by 15,398

A comparative study of texture measures with classification based on featured distributions

Ojala, T., Pietikäinen, M., & Harwood, D. (1996) · Pattern Recognition · doi:10.1016/0031-3203(95)00067-4 · Cited by 6,882

Entropy Balancing for Causal Effects: A Multivariate Reweighting Method to Produce Balanced Samples in Observational Studies

Hainmueller, J. (2012) · Political Analysis · doi:10.1093/pan/mpr025 · Cited by 6,026

Modeling by shortest data description

Rissanen, J. (1978) · Automatica · doi:10.1016/0005-1098(78)90005-5 · Cited by 6,011

Model Selection and Akaike's Information Criterion (AIC): The General Theory and its Analytical Extensions

Bozdogan, H. (1987) · Psychometrika · doi:10.1007/bf02294361 · Cited by 4,468

Sparse coding with an overcomplete basis set: A strategy employed by V1?

Olshausen, B. A., & Field, D. J. (1997) · Vision Research · doi:10.1016/s0042-6989(97)00169-7 · Cited by 3,642

Detection of Abrupt Changes: Theory and Application

Riedel, K. S. (1994) · Technometrics · doi:10.1080/00401706.1994.10485821 · Cited by 3,518

A learning algorithm for Boltzmann machines

Ackley, D. H., Hinton, G. E., & Sejnowski, T. J. (1985) · Cognitive Science · doi:10.1207/s15516709cog0901_7 · Cited by 3,402

Information Theory and an Extension of the Maximum Likelihood Principle

Akaike, H. (1992) · Springer Series in Statistics · doi:10.1007/978-1-4612-0919-5_38 · Cited by 3,028

Knowledge Graph Embedding: A Survey of Approaches and Applications

Wang, Q., Mao, Z., Wang, B., & Guo, L. (2017) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2017.2754499 · Cited by 2,654

Assessing the accuracy of prediction algorithms for classification: an overview

Baldi, P., Brunak, S., Chauvin, Y., Andersen, C. A. F., & Nielsen, H. (2000) · Bioinformatics · doi:10.1093/bioinformatics/16.5.412 · Cited by 2,111

$I$-Divergence Geometry of Probability Distributions and Minimization Problems

Csiszar, I. (1975) · The Annals of Probability · doi:10.1214/aop/1176996454 · Cited by 1,645

4. Regression with Missing Ys: An Improved Strategy for Analyzing Multiply Imputed Data

von Hippel, P. T. (2007) · Sociological Methodology · doi:10.1111/j.1467-9531.2007.00180.x · Cited by 1,495

Statistics and Partitioning of Species Diversity, and Similarity among Multiple Communities

Lande, R. (1996) · Oikos · doi:10.2307/3545743 · Cited by 1,409

Group representations in probability and statistics

Diaconis, P. (1988) · doi:10.1214/lnms/1215467407 · Cited by 1,381

Bayesian surprise attracts human attention

Itti, L., & Baldi, P. (2009) · Vision Research · doi:10.1016/j.visres.2008.09.007 · Cited by 1,224

The helmholtz machine

Dayan, P., Hinton, G. E., Neal, R. M., & Zemel, R. S. (1995) · Neural Computation · doi:10.1162/neco.1995.7.5.889 · Cited by 1,207

The mutual information: detecting and evaluating dependencies between variables

Steuer, R., Kurths, J., Daub, C. O., Weise, J., & Selbig, J. (2002) · Bioinformatics · doi:10.1093/bioinformatics/18.suppl_2.s231 · Cited by 815

Stochastic Computing Systems

Gaines, B. R. (1969) · Advances in Information Systems Science · doi:10.1007/978-1-4899-5841-9_2 · Cited by 745

Extra-dimensional versus intra-dimensional set shifting performance following frontal lobe excisions, temporal lobe excisions or amygdalo-hippocampectomy in man

Owen, A. M., Roberts, A. C., Polkey, C. E., Sahakian, B. J., & Robbins, T. W. (1991) · Neuropsychologia · doi:10.1016/0028-3932(91)90063-e · Cited by 657

Equitability, mutual information, and the maximal information coefficient

Kinney, J. B., & Atwal, G. S. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1309933111 · Cited by 667

Completely positive maps and entropy inequalities

Lindblad, G. (1975) · Communications in Mathematical Physics · doi:10.1007/bf01609396 · Cited by 666

A Bayesian Truth Serum for Subjective Data

Prelec, D. (2004) · Science · doi:10.1126/science.1102081 · Cited by 530

Impaired extra-dimensional shift performance in medicated and unmedicated Parkinson's disease: Evidence for a specific attentional dysfunction

Downes, J. J., Roberts, A. C., Sahakian, B. J., Evenden, J. L., Morris, R. G., & Robbins, T. W. (1989) · Neuropsychologia · doi:10.1016/0028-3932(89)90128-0 · Cited by 527

Quasi-entropies for finite quantum systems

Petz, D. (1986) · Reports on Mathematical Physics · doi:10.1016/0034-4877(86)90067-4 · Cited by 500

A Sequential Theory of Psychological Discrimination

Link, S. W., & Heath, R. A. (1975) · Psychometrika · doi:10.1007/bf02291481 · Cited by 492

Computational Mechanics: Pattern and Prediction, Structure and Simplicity

Shalizi, C. R., & Crutchfield, J. P. (2001) · Journal of Statistical Physics · doi:10.1023/a:1010388907793 · Cited by 471

Quantifying causal emergence shows that macro can beat micro

Hoel, E. P., Albantakis, L., & Tononi, G. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1314922110 · Cited by 378

AN OLD‐NEW CONCEPT OF CONVEX RISK MEASURES: THE OPTIMIZED CERTAINTY EQUIVALENT

Ben‐Tal, A., & Teboulle, M. (2007) · Mathematical Finance · doi:10.1111/j.1467-9965.2007.00311.x · Cited by 353

Dopaminergic and serotonergic function following isolation rearing in rats: study of behavioural responses and postmortem and in vivo neurochemistry

Jones, G. H., Hernandez, T. D., Kendall, D. A., Marsden, C. A., & Robbins, T. W. (1992) · Pharmacology Biochemistry and Behavior · doi:10.1016/0091-3057(92)90635-s · Cited by 341

Tryptophan depletion impairs stimulus-reward learning while methylphenidate disrupts attentional control in healthy young adults: implications for the monoaminergic basis of impulsive behaviour

Rogers, R. D., Blackshaw, A. J., Middleton, H. C., Matthews, K., Hawtin, K., Crowley, C., Hopwood, A., Wallace, C., Deakin, J. F. W., Sahakian, B. J., et al. (1999) · Psychopharmacology · doi:10.1007/pl00005494 · Cited by 289

Covariation of mutations in the v3 loop of human immunodeficiency virus type 1 envelope protein: an information theoretic analysis

Korber, B. T., Farber, R. M., Wolpert, D. H., & Lapedes, A. S. (1993) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.90.15.7176 · Cited by 257

Distinct Profiles of Neurocognitive Function in Unmedicated Unipolar Depression and Bipolar II Depression

Taylor Tavares, J. V., Clark, L., Cannon, D. M., Erickson, K., Drevets, W. C., & Sahakian, B. J. (2007) · Biological Psychiatry · doi:10.1016/j.biopsych.2007.05.034 · Cited by 262

Specific cognitive deficits in tests sensitive to frontal lobe dysfunction in obsessive-compulsive disorder

Veale, D. M., Sahakian, B. J., Owen, A. M., & Marks, I. M. (1996) · Psychological Medicine · doi:10.1017/s0033291700035984 · Cited by 239

Hybrid physics-informed neural networks for lithium-ion battery modeling and prognosis

Nascimento, R. G., Corbetta, M., Kulkarni, C. S., & Viana, F. A. C. (2021) · Journal of Power Sources · doi:10.1016/j.jpowsour.2021.230526 · Cited by 224

Executive function in Tourette’s syndrome and obsessive–compulsive disorder

WATKINS, L. H., SAHAKIAN, B. J., ROBERTSON, M. M., VEALE, D. M., ROGERS, R. D., PICKARD, K. M., AITKEN, M. R. F., & ROBBINS, T. W. (2005) · Psychological Medicine · doi:10.1017/s0033291704003691 · Cited by 210

Natural selection for least action

Kaila, V. R. I., & Annila, A. (2008) · Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences · doi:10.1098/rspa.2008.0178 · Cited by 153

Bladder cancer SNP panel predicts susceptibility and survival

Andrew, A. S., Gui, J., Sanderson, A. C., Mason, R. A., Morlock, E. V., Schned, A. R., Kelsey, K. T., Marsit, C. J., Moore, J. H., & Karagas, M. R. (2009) · Human Genetics · doi:10.1007/s00439-009-0645-6 · Cited by 98

Retarded acquisition and reduced expression of conditioned locomotor activity in adult rats following repeated early maternal separation: effects of prefeeding,d-amphetamine, dopamine antagonists and clonidine

Matthews, K., Hall, F. S., Wilkinson, L. S., & Robbins, T. W. (1996) · Psychopharmacology · doi:10.1007/bf02246414 · Cited by 93

Introducing a Bayesian model of selective attention based on active inference

Mirza, M. B., Adams, R. A., Friston, K., & Parr, T. (2019) · Scientific Reports · doi:10.1038/s41598-019-50138-8 · Cited by 83

Neural coding and decoding: communication channels and quantization

Dimitrov, A. G., & Miller, J. P. (2001) · Network: Computation in Neural Systems · doi:10.1080/net.12.4.441.472 · Cited by 76

Visual adaptation and novelty responses in the superior colliculus: Adaptation in the SC

Boehnke, S. E., Berg, D. J., Marino, R. A., Baldi, P. F., Itti, L., & Munoz, D. P. (2011) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2011.07805.x · Cited by 60

Thermodynamic length for far-from-equilibrium quantum systems

Deffner, S., & Lutz, E. (2013) · Physical Review E · doi:10.1103/physreve.87.022143 · Cited by 56

A measure for intrinsic information

Barbosa, L. S., Marshall, W., Streipert, S., Albantakis, L., & Tononi, G. (2020) · Scientific Reports · doi:10.1038/s41598-020-75943-4 · Cited by 42

Improving astronaut cancer risk assessment from space radiation with an ensemble model framework

Simonsen, L. C., & Slaba, T. C. (2021) · Life Sciences in Space Research · doi:10.1016/j.lssr.2021.07.002 · Cited by 36

Combining Gameplay Data with Monte Carlo Tree Search to Emulate Human Play

Devlin, S., Anspoka, A., Sephton, N., Cowling, P., & Rollason, J. (2016) · Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment · doi:10.1609/aiide.v12i1.12858 · Cited by 28

Moment information and entropy evaluation for probability densities

Milev, M., Inverardi, P. N., & Tagliani, A. (2012) · Applied Mathematics and Computation · doi:10.1016/j.amc.2011.11.093 · Cited by 24

The characterization of a measure of information discrepancy

Fang, W. (2000) · Information Sciences · doi:10.1016/s0020-0255(00)00008-6 · Cited by 23

Time Series Regression and Exploratory Data Analysis

Shumway, R. H., & Stoffer, D. S. (2017) · Springer Texts in Statistics · doi:10.1007/978-3-319-52452-8_2 · Cited by 13

Entropy and Uncertainty Analysis in Financial Markets

Dionisio, A., Menezes, R., & Mendes, D. A. (2007) · arXiv · doi:10.48550/arxiv.0709.0668 · Cited by 13

Hypothesis testing with active information

Díaz–Pachón, D. A., Sáenz, J. P., & Rao, J. S. (2020) · Statistics & Probability Letters · doi:10.1016/j.spl.2020.108742 · Cited by 12

Communication-efficient hierarchical federated learning for IoT heterogeneous systems with imbalanced data

Abdellatif, A. A., Mhaisen, N., Mohamed, A., Erbad, A., Guizani, M., Dawy, Z., & Nasreddine, W. (2022) · Future Generation Computer Systems · doi:10.1016/j.future.2021.10.016 · Cited by 4

Predictive efficiency for simple non-linear models

Cooley, T. F., Parke, W. R., & Chib, S. (1989) · Journal of Econometrics · doi:10.1016/0304-4076(89)90028-6 · Cited by 3