Probability and Random Processes.

Computational modeling of therapy on pancreatic cancer in its early stages

Chen, J., Weihs, D., & Vermolen, F. J. (2019) · Biomechanics and Modeling in Mechanobiology · doi:10.1007/s10237-019-01219-0 · Cited by 25

CoMP-NOMA in the SWIPT Networks

Hedayati, M., & Kim, I. (2020) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2020.2985038 · Cited by 25

Recursive Total Least-Squares Algorithm Based on Inverse Power Method and Dichotomous Coordinate-Descent Iterations

Arablouei, R., Doğançay, K., & Werner, S. (2015) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2015.2405492 · Cited by 25

Does the bond‐stock earnings yield differential model predict equity market corrections better than high P/E models?

Lleo, S., & Ziemba, W. T. (2017) · Financial Markets Institutions and Instruments · doi:10.1111/fmii.12080 · Cited by 25

Handling Experimental Data

Prügel‐Bennett, A. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108635349.007 · Cited by 25

Adjoint-based deviational Monte Carlo methods for phonon transport calculations

Péraud, J.-P. M., & Hadjiconstantinou, N. G. (2015) · Physical Review B · doi:10.1103/physrevb.91.235321 · Cited by 21

An RF Carrier Bursting System Using Partial Quantization Noise Cancellation

Gustavsson, U., Eriksson, T., Nemati, H. M., et al. (2011) · IEEE Transactions on Circuits and Systems I Regular Papers · doi:10.1109/tcsi.2011.2167271 · Cited by 24

Vehicle actuated signal performance under general traffic at an isolated intersection

Wang, X. B., Yin, K., & Liu, H. X. (2018) · Transportation Research Part C Emerging Technologies · doi:10.1016/j.trc.2018.08.002 · Cited by 24

Frailty status among older critically ill patients with severe acute kidney injury

Beaubien‐Souligny, W., Yang, A., Lebovic, G., et al. (2021) · Critical Care · doi:10.1186/s13054-021-03510-y · Cited by 24

The stationary distribution of a continuously varying strategy in a class‐structured population under mutation–selection–drift balance

Lehmann, L. (2012) · Journal of Evolutionary Biology · doi:10.1111/j.1420-9101.2012.02472.x · Cited by 23

Potential games in volatile environments

Staudigl, M. (2010) · Games and Economic Behavior · doi:10.1016/j.geb.2010.08.004 · Cited by 22

Modelling the flow of congestive heart failure patients through a hospital system

Shaw, B., & Marshall, A. H. (2006) · Journal of the Operational Research Society · doi:10.1057/palgrave.jors.2602240 · Cited by 24

SOME RESULTS FOR SKIP-FREE RANDOM WALK

Brown, M., Peköz, E. A., & Ross, S. M. (2010) · Probability in the Engineering and Informational Sciences · doi:10.1017/s0269964810000136 · Cited by 24

Traffic Modeling and Optimization in Public and Private Wireless Access Networks for Smart Grids

Al-Khatib, O., Hardjawana, W., & Vucetic, B. S. (2014) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2014.2304495 · Cited by 24

Distributed Detection in UWB Wireless Sensor Networks

Bai, K., & Tepedelenlioğlu, C. (2009) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2009.2027776 · Cited by 24

A Duality Framework for Stochastic Optimal Control of Complex Systems

Malikopoulos, A. A. (2015) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2015.2504518 · Cited by 24

Burstiness of Intrusion Detection Process: Empirical Evidence and a Modeling Approach

Harang, R., & Kott, A. (2017) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2017.2705629 · Cited by 24

Data analytic approach for manipulation detection in stock market

Zhai, J., Cao, Y., & Ding, X. (2017) · Review of Quantitative Finance and Accounting · doi:10.1007/s11156-017-0650-0 · Cited by 24

Energy Saving and Reliability for Wireless Body Sensor Networks (WBSN)

Alshaheen, H., & Takruri‐Rizk, H. (2018) · IEEE Access · doi:10.1109/access.2018.2817025 · Cited by 24

A methodological framework for cloud resource provisioning and scheduling of data parallel applications under uncertainty

Calzarossa, M. C., Vedova, M. L. D., & Tessera, D. (2018) · Future Generation Computer Systems · doi:10.1016/j.future.2018.10.037 · Cited by 24

Computer Model Calibration with Confidence and Consistency

Plumlee, M. (2019) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/rssb.12314 · Cited by 24

A stochastic T cell response criterion

Currie, J., Castro, M., Lythe, G., Palmer, E., & Molina-Parı́s, C. (2012) · Journal of The Royal Society Interface · doi:10.1098/rsif.2012.0205 · Cited by 24

Adaptive play by idiosyncratic agents

Myatt, D. P., & Wallace, C. (2003) · Games and Economic Behavior · doi:10.1016/j.geb.2003.07.004 · Cited by 23

Microeconomic Origins of Macroeconomic Tail Risks

Acemoğlu, D., Ozdaglar, A., & Tahbaz-Salehi, A. (2015) · National Bureau of Economic Research · doi:10.3386/w20865 · Cited by 24

First-hitting times under drift

Kötzing, T., & Krejca, M. S. (2019) · Theoretical Computer Science · doi:10.1016/j.tcs.2019.08.021 · Cited by 23

Sampling-based planning for non-myopic multi-robot information gathering

Kantaros, Y., Schlotfeldt, B., Atanasov, N., & Pappas, G. J. (2021) · Autonomous Robots · doi:10.1007/s10514-021-09995-4 · Cited by 23

The formation of networks with local spillovers and limited observability

König, M. (2016) · Theoretical Economics · doi:10.3982/te1524 · Cited by 23

Contour-based 3D Face Modeling from a Monocular Video

Gupta, H., Roy-chowdhury, A. K., & Chellapa, R. (2004) · British Machine Vision Conference (BMVC) · doi:10.5244/c.18.39 · Cited by 23

Context-Aware Elevator Scheduling

Strang, T., & Bauer, C. (2007) · International Conference on Advanced Information Networking and Applications Workshops (WAINA) · doi:10.1109/ainaw.2007.131 · Cited by 23

The robustness of the weak selection approximation for the evolution of altruism against strong selection

Mullon, C., & Lehmann, L. (2014) · Journal of Evolutionary Biology · doi:10.1111/jeb.12462 · Cited by 25

Delay Guarantees for Throughput-Optimal Wireless Link Scheduling

Kar, K., Sarkar, S. S., Ghavami, A., et al. (2012) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2012.2194333 · Cited by 23

Energy-Delay Tradeoff and Dynamic Sleep Switching for Bluetooth-Like Body-Area Sensor Networks

Rebeiz, E., Caire, G., & Molisch, A. F. (2012) · IEEE Transactions on Communications · doi:10.1109/tcomm.2012.12.110143a · Cited by 23

Non-asymptotic throughput and delay distributions in multi-hop wireless networks

Ciucu, F., Hohlfeld, O., & Hui, P. (2010) · Allerton Conference on Communication, Control, and Computing · doi:10.1109/allerton.2010.5706970 · Cited by 23

Modulation of gene transcription noise by competing transcription factors

Sun, Q., Tang, M., & Yu, J. (2011) · Journal of Mathematical Biology · doi:10.1007/s00285-011-0420-x · Cited by 22

On the selection of semi-orthogonal users for zero-forcing beamforming

Tomasoni, A., Caire, G., Ferrari, M., et al. (2009) · IEEE International Symposium on Information Theory (ISIT) · doi:10.1109/isit.2009.5206033 · Cited by 23

Smoothing policies and safe policy gradients

Papini, M., Pirotta, M., & Restelli, M. (2022) · Machine Learning · doi:10.1007/s10994-022-06232-6 · Cited by 25

Approaches to evaluating measurement uncertainty

Forbes, A. (2012) · International Journal of Metrology and Quality Engineering · doi:10.1051/ijmqe/2012017 · Cited by 23

Stochastic competitive exclusion in the maintenance of the naïve T cell repertoire

Stirk, E. R., Lythe, G., van den Berg, H. A., & Molina-Parı́s, C. (2010) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2010.05.004 · Cited by 23

Optimal Quantization of Signals for System Identification

Tsumura, K. (2009) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2009.2033859 · Cited by 23

Optimal sensing interval in cognitive radio networks with imperfect spectrum sensing

Liu, B., Li, Z., Si, J., et al. (2016) · IET Communications · doi:10.1049/iet-com.2015.0671 · Cited by 22

Optimal Sensor Collaboration for Parameter Tracking Using Energy Harvesting Sensors

Zhang, S., Liu, S., Sharma, V., et al. (2018) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2018.2827319 · Cited by 22

Spectral Complexity of Directed Graphs and Application to Structural Decomposition

Mezić, I., Fonoberov, V. A., Fonoberova, M., & Sahai, T. (2019) · Complexity · doi:10.1155/2019/9610826 · Cited by 24

Redundancy scheduling with scaled Bernoulli service requirements

Raaijmakers, Y. Y., Borst, S. S. =. S., & Boxma, O. O. (2019) · TU/e Research Portal · Cited by 22

On Scaling Laws of Diversity Schemes in Decentralized Estimation

Leong, A. S., & Dey, S. (2011) · IEEE Transactions on Information Theory · doi:10.1109/tit.2011.2146070 · Cited by 22

Estimation of parameters in large offspring number models and ratios of coalescence times

Eldon, B. (2011) · Theoretical Population Biology · doi:10.1016/j.tpb.2011.04.002 · Cited by 22

Expected Routing Overhead for Location Service in MANETs under Flat Geographic Routing

La, R. J., & Seo, E. (2010) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2010.188 · Cited by 22

A Polya Contagion Model for Networks

Hayhoe, M., Alajaji, F., & Gharesifard, B. (2017) · IEEE Transactions on Control of Network Systems · doi:10.1109/tcns.2017.2781467 · Cited by 22

Uncertainty quantification of elastic material responses: testing, stochastic calibration and Bayesian model selection

Fitt, D., Wyatt, H., Woolley, T. E., & Mihai, L. A. (2019) · Mechanics Of Soft Materials · doi:10.1007/s42558-019-0013-1 · Cited by 22

Non-Gaussian probabilistic MEG source localisation based on kernel density estimation

Mohseni, H., Kringelbach, M. L., Woolrich, M. W., et al. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.09.012 · Cited by 22

Analysis of Single‐Molecule Fluorescence Spectroscopic Data with a Markov‐Modulated Poisson Process

Jäger, M., Kiel, A., Herten, D., & Hamprecht, F. A. (2009) · ChemPhysChem · doi:10.1002/cphc.200900331 · Cited by 22

Entanglement in the Quantum Ising Model

Grimmett, G. R., Osborne, T. J., & Scudo, P. F. (2008) · Journal of Statistical Physics · doi:10.1007/s10955-008-9502-6 · Cited by 24

Machine Learning for Signal Processing

Little, M. A. (2019) · doi:10.1093/oso/9780198714934.001.0001 · Cited by 33

Incorporating environmental stochasticity within a biological population model

Varughese, M., & Fatti, L. P. (2008) · Theoretical Population Biology · doi:10.1016/j.tpb.2008.05.004 · Cited by 22

Principle Components and Importance Ranking of Distributed Anomalies

Begnum, K., & Burgess, M. (2005) · Machine Learning · doi:10.1007/s10994-005-5827-4 · Cited by 22

Opportunistic scheduling for streaming users in high-speed downlink packet access (HSDPA)

Farrokh, A., & Krishnamurthy, V. (2005) · IEEE Global Telecommunications Conference (GLOBECOM) · doi:10.1109/glocom.2004.1379126 · Cited by 22

A Dynamic Model of Network Formation with Strategic InteractionsPreprint

König, M., Tessone, C. J., & Zénou, Y. (2010) · SSRN Electronic Journal · doi:10.2139/ssrn.1596004 · Cited by 23

Robust Generation Dispatch With Purchase of Renewable Power and Load Predictions

Xie, R., Pinson, P., Xu, Y., et al. (2024) · IEEE Transactions on Sustainable Energy · doi:10.1109/tste.2024.3353779 · Cited by 21

Benchmarking hybrid algorithms for distributed constraint optimisation games

Chapman, A. C., Rogers, A., & Jennings, N. R. (2010) · Autonomous Agents and Multi-Agent Systems · doi:10.1007/s10458-010-9128-3 · Cited by 21

Modeling Heterogeneous Virtual Machines on IaaS Data Centers

Wang, B., Chang, X., & Liu, J. (2015) · IEEE Communications Letters · doi:10.1109/lcomm.2015.2403832 · Cited by 21

Specific Differential Entropy Rate Estimation for Continuous-Valued Time Series

Darmon, D. M. (2016) · Entropy · doi:10.3390/e18050190 · Cited by 21

Redundancy scheduling with scaled Bernoulli service requirements

Raaijmakers, Y., Borst, S., & Boxma, O. (2019) · Queueing Systems · doi:10.1007/s11134-019-09621-2 · Cited by 21

Extracting complements and substitutes from sales data: a network perspective

Tian, Y., Lautz, S., Wallis, A. O. G., et al. (2021) · EPJ Data Science · doi:10.1140/epjds/s13688-021-00297-4 · Cited by 21

Convergence of the Huber Regression M-Estimate in the Presence of Dense Outliers

Tsakonas, E., Jaldén, J., Sidiropoulos, N. D., et al. (2014) · IEEE Signal Processing Letters · doi:10.1109/lsp.2014.2329811 · Cited by 21

Additive and exclusive noise suppression by iterative trimmed and truncated mean algorithm

Miao, Z., & Jiang, X. (2013) · Signal Processing · doi:10.1016/j.sigpro.2013.12.002 · Cited by 21

Reversibility and oscillations in zero-sum discounted stochastic games

Sorin, S., & Vigeral, G. (2015) · Journal of Dynamics and Games · doi:10.3934/jdg.2015.2.103 · Cited by 21

The mean and noise of protein numbers in stochastic gene expression

Kuang, J., Tang, M., & Yu, J. (2012) · Journal of Mathematical Biology · doi:10.1007/s00285-012-0551-8 · Cited by 21

Limit Theorems for a Generalized Feller Game

Matsumoto, K., & Nakata, T. (2013) · Journal of Applied Probability · doi:10.1239/jap/1363784424 · Cited by 21

Consistent Event-Triggered Control for Discrete-Time Linear Systems With Partial State Information

Antunes, D., & Balaghiinaloo, M. (2019) · IEEE Control Systems Letters · doi:10.1109/lcsys.2019.2922187 · Cited by 21

FSTruct : An F ST ‐based tool for measuring ancestry variation in inference of population structure

Morrison, M. L., Alcala, N., & Rosenberg, N. A. (2022) · Molecular Ecology Resources · doi:10.1111/1755-0998.13647 · Cited by 20

On the multi-splitting iteration method for computing PageRank

Gu, C., & Wang, L. (2013) · Journal of Applied Mathematics and Computing · doi:10.1007/s12190-013-0645-5 · Cited by 20

Temporal Profile of Gene Transcription Noise Modulated by Cross-Talking Signal Transduction Pathways

Sun, Q., Tang, M., & Yu, J. (2011) · Bulletin of Mathematical Biology · doi:10.1007/s11538-011-9683-z · Cited by 19

Modelling dispersal with diffusion and habitat selection: Analytical results for highly fragmented landscapes

Zheng, C., Pennanen, J., & Ovaskainen, O. (2009) · Ecological Modelling · doi:10.1016/j.ecolmodel.2009.02.024 · Cited by 20

The effectiveness of the linear hull effect

Murphy, S. P. (2012) · Journal of Mathematical Cryptology · doi:10.1515/jmc-2011-0025 · Cited by 20

AN EVOLUTIONARY APPROACH FOR IMPUTING MISSING DATA IN TIME SERIES

Figueroa–García, J. C., Kalenatic, D., & Bello, C. A. L. (2010) · Journal of Circuits Systems and Computers · doi:10.1142/s0218126610006050 · Cited by 20

A Hybrid Monte Carlo Scheme for Multibackbone Protein Design

Druart, K., Bigot, J., Audit, E., & Simonson, T. (2016) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.6b00421 · Cited by 20

Identification of FIR Systems With Binary Input and Output Observations

Leong, A. S., Weyer, E., & Nair, G. N. (2016) · Proceedings of the IEEE Conference on Decision & Control, including the Symposium on Adaptive Processes · doi:10.1109/cdc.2016.7798706 · Cited by 20

Statistical feature analysis for EEG baseline classification: Eyes Open vs Eyes Closed

Gopika Gopan, K., Sinha, N., & Dinesh Babu, J. (2016) · IEEE Region 10 Conference (TENCON) · doi:10.1109/tencon.2016.7848476 · Cited by 20

Decomposition of quantum Markov chains and its applications

Guan, J., Feng, Y., & Ying, M. (2018) · Journal of Computer and System Sciences · doi:10.1016/j.jcss.2018.01.005 · Cited by 19

The Chain Length Distribution of an Ideal Reversible Deactivation Radical Polymerization

Harrisson, S. (2018) · Polymers · doi:10.3390/polym10080887 · Cited by 20

Simulation and Real-World Evaluation of Attack Detection Schemes

Porter, M., Joshi, A., Hespanhol, P., et al. (2019) · Proceedings of the ... American Control Conference/Proceedings of the American Control Conference · doi:10.23919/acc.2019.8815318 · Cited by 20

Encoder-Assisted Communications Over Additive Noise Channels

Lapidoth, A., & Marti, G. (2020) · IEEE Transactions on Information Theory · doi:10.1109/tit.2020.3012629 · Cited by 20

Approximating the longest path length of a stochastic DAG by a normal distribution in linear time

Ando, E., Nakata, T., & Yamashita, M. (2009) · Journal of Discrete Algorithms · doi:10.1016/j.jda.2009.01.001 · Cited by 20

Directed Random Dot Product Graphs

Young, S. J., & Scheinerman, E. (2008) · Internet Mathematics · doi:10.1080/15427951.2008.10129301 · Cited by 20

First in Line Waiting Times as a Tool for Analysing Queueing Systems

Koole, G. M., Nielsen, B. F., & Nielsen, T. B. (2012) · Operations Research · doi:10.1287/opre.1120.1089 · Cited by 20

Collective behavior and predation success in a predator-prey model inspired by hunting bats

Lin, Y., & Abaid, N. (2013) · Physical Review E · doi:10.1103/physreve.88.062724 · Cited by 19

Achievable Rates for Channels With Deletions and Insertions

Venkataramanan, R., Tatikonda, S., & Ramchandran, K. (2013) · IEEE Transactions on Information Theory · doi:10.1109/tit.2013.2278181 · Cited by 20

Kalman filtering over a packet dropping network: A probabilistic approach

Shi, L., Epstein, M., & Murray, R. M. (2008) · International Conference on Control, Automation, Robotics and Vision (ICARCV) · doi:10.1109/icarcv.2008.4795489 · Cited by 20

Retrenching the Purse: Finite Sequence Numbers, and the Tower Pattern

Banach, R., Poppleton, M. R., Jeske, C., et al. (2005) · Lecture notes in computer science · doi:10.1007/11526841_26 · Cited by 20

An algorithm for sampling subsets of H/sub /spl infin// with applications to risk-adjusted performance analysis and model (in)validation

Sznaier, M., Lagoa, C. M., & Mazzaro, M. C. (2005) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2005.843852 · Cited by 20

Random non-autonomous second order linear differential equations: mean square analytic solutions and their statistical properties

Calatayud, J., Cortés, J. ‐., Jornet, M., et al. (2018) · Advances in Difference Equations · doi:10.1186/s13662-018-1848-8 · Cited by 19

The SNR of a transit

Kipping, D. (2023) · Monthly Notices of the Royal Astronomical Society · doi:10.1093/mnras/stad1492 · Cited by 19

Kriging Prediction Intervals Based on Semiparametric Bootstrap

Schelin, L., & de Luna, S. S. (2010) · Mathematical Geosciences · doi:10.1007/s11004-010-9302-9 · Cited by 19

Wireless Network Control of Interacting Rydberg Atoms

Sanders, J., van Bijnen, R., Vredenbregt, E. J. D., et al. (2014) · Physical Review Letters · doi:10.1103/physrevlett.112.163001 · Cited by 19

Consensus problem under diffusion-based molecular communication

Einolghozati, A., Sardari, M., Beirami, A., et al. (2011) · Conference on Information Sciences and Systems · doi:10.1109/ciss.2011.5766149 · Cited by 19

Asymptotic Analysis of Proportionally Fair Scheduling in Rayleigh Fading

Liu, E., Zhang, Q., & Leung, K. K. (2011) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2011.032411.100461 · Cited by 19

Decentralized Throughput Maximization in Cognitive Radio Wireless Mesh Networks

El-Sherif, A. A., & Mohamed, A. M. S. (2014) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2013.82 · Cited by 19

Chiral charge erasure via thermal fluctuations of magnetic helicity

Long, A. J., & Sabancilar, E. (2016) · Journal of Cosmology and Astroparticle Physics · doi:10.1088/1475-7516/2016/05/029 · Cited by 21

Microwave Measurement System for Detection of Dielectric Objects in Powders

Nohlert, J., Rylander, T., & McKelvey, T. (2016) · IEEE Transactions on Microwave Theory and Techniques · doi:10.1109/tmtt.2016.2613047 · Cited by 19

Computational Design of the Tiam1 PDZ Domain and Its Ligand Binding

Mignon, D., Panel, N., Chen, X., Fuentes, E. J., & Simonson, T. (2017) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.6b01255 · Cited by 19

Computing Expected Runtimes for Constant Probability Programs

Giesl, J., Giesl, P., & Hark, M. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-29436-6_16 · Cited by 19

On Inter-using of Probability Theory and Mathematical Analysis in Solving the Problem

Liu, M. (2006)

The Design of Review about the Course "Probability Theory"

He, J. (2009) · Journal of Mudanjiang College of Education

Genesis and Development and Applications of Theory of Probability

Xu, H. M. (2001) · Journal of Liaoning Institute of Technology On Social Science

Applications of probability and statistical theory

Edgeworth, F. Y., & McCann, C. R. (1996) · Medical Entomology and Zoology

Some Thoughts about Application of Concept Maps in Teaching Probability Theory and Mathematical Statistics

Jie, Z. (2007) · Journal on Mathematics Education · Cited by 1