I. Meilijson

Isaac Meilijson, Eytan Ruppin, Alon Keinan, 2003, Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

Localization of Function via Lesion Analysis

Isaac Meilijson, Eytan Ruppin, Ranit Aharonov-Barki, 2003, Neural Computation.

The signal model: A model for competing risks of opportunistic maintenance

Athena Zitrou, Isaac Meilijson, Tim Bedford, 2011, Eur. J. Oper. Res..

A consignment contract with revenue sharing between an app developer and a distribution platform

I. Meilijson, Tatyana Chernonog, Tal Avinadav, 2021, International Journal of Production Economics.

Parameter estimation in differential equations, using random time transformations

I. Meilijson, R. Marcus, H. Talpaz, 1997 .

The stealthy nano-machine behind mast cell granule size distribution.

I. Meilijson, I. Hammel, 2015, Molecular immunology.

Who Does What? A Novel Algorithm to Determine Function Localization

Isaac Meilijson, Eytan Ruppin, Ranit Aharonov-Barki, 2000, NIPS.

Migration rather than proliferation transcriptomic signatures are strongly associated with breast cancer patient survival

Sylvia E. Le Dévédec, E. Ruppin, I. Meilijson, 2018, Scientific Reports.

A Ribosome Flow Model for Analyzing Translation Elongation - (Extended Abstract)

Isaac Meilijson, Eytan Ruppin, Tamir Tuller, 2011, RECOMB.

Quantitative Analysis of Genetic and Neuronal Multi-Perturbation Experiments

Isaac Meilijson, Eytan Ruppin, Martin Kupiec, 2005, PLoS Comput. Biol..

Evolution of Reinforcement Learning in Uncertain Environments: A Simple Explanation for Complex Foraging Behaviors

Isaac Meilijson, Eytan Ruppin, Yael Niv, 2002, Adapt. Behav..

High-Dimensional Analysis of Evolutionary Autonomous Agents

Isaac Meilijson, Eytan Ruppin, Ranit Aharonov-Barki, 2002, Artificial Life.

Optimal Signalling in Attractor Neural Networks

Isaac Meilijson, Eytan Ruppin, E. Ruppin, 1993, NIPS.

History-Dependent Attractor Neural Networks

Isaac Meilijson, Eytan Ruppin, E. Ruppin, 1992, NIPS.

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E. Ruppin, I. Meilijson, L. Segev, 2007 .

High-Dimensional Analysis of EvolutionaryAutonomous

R. Aharonov, E. Ruppin, I. Meilijson, 2004 .

Maturation of the humoral immune response as an optimization problem

I. Meilijson, Z. Agur, G. Mazor, 1991, Proceedings of the Royal Society of London. Series B: Biological Sciences.

Can single knockouts accurately single out gene functions?

Isaac Meilijson, Eytan Ruppin, Stefan Schuster, 2008, BMC Systems Biology.

Preference for safety under the Choquet model: in search of a characterization

I. Meilijson, Michèle Cohen, M. Cohen, 2014 .

THE RE-OPENING OF DUBINS AND SAVAGE CASINO IN THE ERA OF DIVERSIFICATION

I. Meilijson, 2013, Probability in the Engineering and Informational Sciences.

Four notions of mean-preserving increase in risk, risk attitudes and applications to the rank-dependent expected utility model

Isaac Meilijson, Alain Chateauneuf, I. Meilijson, 2004 .

Neuronal Regulation: A Mechanism for Synaptic Pruning During Brain Maturation

Isaac Meilijson, Eytan Ruppin, Gal Chechik, 1999, Neural Computation.

A Note on Sequential Multiple Decision Procedures

I. Meilijson, 1969 .

More pessimism than greediness: a characterization of monotone risk aversion in the rank-dependent expected utility model

Isaac Meilijson, M. Cohen, A. Chateauneuf, 2005 .

Number of matches and matched people in the birthday problem

Isaac Meilijson, Uri Yechiali, Aaron Tenenbein, 1982 .

Intertemporal Price Discrimination and Sales Strategy under Incomplete Information

Isaac Meilijson, Michael Landsberger, I. Meilijson, 1985 .

Demand for risky financial assets: A portfolio analysis

Isaac Meilijson, Michael Landsberger, I. Meilijson, 1990 .

A general model of insurance under adverse selection

Isaac Meilijson, Michael Landsberger, I. Meilijson, 1999 .

Extraction of Surplus under Adverse Selection: The Case of Insurance Markets

I. Meilijson, M. Landsberger, 1996 .

Monopoly Insurance under Adverse Selection When Agents Differ in Risk Aversion

Isaac Meilijson, Michael Landsberger, I. Meilijson, 1994 .

Synaptic pruning in development: a novel account in neural terms

Isaac Meilijson, Eytan Ruppin, Gal Chechik, 1998 .

Synaptic Pruning in Development: A Computational Account

Isaac Meilijson, Eytan Ruppin, Gal Chechik, 1998, Neural Computation.

Distributed synchrony in a cell assembly of spiking neurons

Isaac Meilijson, Eytan Ruppin, Nir Levy, 2001, Neural Networks.

Lotteries, insurance, and star-shaped utility functions

I. Meilijson, M. Landsberger, 1990 .

For how long do trans-Saharan migrants stop over at an oasis ?

I. Meilijson, U. Safriel, D. Lavee, 1991 .

Function suggests nano-structure: electrophysiology supports that granule membranes play dice

I. Meilijson, I. Hammel, 2012, Journal of The Royal Society Interface.

Quantal basis of vesicle growth and information content, a unified approach.

I. Meilijson, Eyal Nitzany, I. Hammel, 2010, Journal of theoretical biology.

Multiple feedback at a single server station

Gideon Weiss, Isaac Meilijson, I. Meilijson, 1975, Advances in Applied Probability.

Splitting matters: how monotone transformation of predictor variables may improve the predictions of decision tree models pdf

Isaac Meilijson, Tal Galili, I. Meilijson, 2016, ArXiv.

An Example of an Improvable Rao–Blackwell Improvement, Inefficient Maximum Likelihood Estimator, and Unbiased Generalized Bayes Estimator

Isaac Meilijson, Tal Galili, I. Meilijson, 2016, The American statistician.

The Garman-Klass volatility estimator revisited

I. Meilijson, 2008, 0807.3492.

The proposed variance estimator vis à vis Garman – Klass

I. Meilijson, 2008 .

Function Suggests Nano-Structure: Quantitative Structural Support for SNARE-Mediated Pore Formation

I. Meilijson, I. Hammel, 2015, Neurotoxicity Research.

Coping with participant heterogeneity in dichotomous responses

I. Meilijson, S. Meilijson, 2009, Statistics in medicine.

The subject of competing risks deals with a machine or a living being which is subject to m competing causes of death, the ith of which would have caused

I. Meilijson, 1981 .

On optimal right-of-way policies at a single-server station when insertion of idle times is permitted

Isaac Meilijson, Uri Yechiali, U. Yechiali, 1977 .

Gene Expression of Caenorhabditis elegans Neurons Carries Information on Their Synaptic Connectivity

Isaac Meilijson, Eytan Ruppin, Gideon Dror, 2006, PLoS Comput. Biol..

Quantal Basis of Secretory Granule Biogenesis and Inventory Maintenance: the Surreptitious Nano-machine Behind It

I. Meilijson, I. Hammel, 2014, Discoveries.

Localization of function in neurocontrollers

Isaac Meilijson, Eytan Ruppin, Ranit Aharonov, 2002 .

Analyzing brain data by sex: Are we asking the right question?

D. Joel, I. Meilijson, Nitay Alon, 2020, bioRxiv.

On the expected diameter of an L2-bounded martingale

L. Dubins, I. Meilijson, D. Gilat, 2008, 0807.3571.

Prices of financial instruments with stochastic volatility

I. Meilijson, B. Sackler, 2006 .

Mixing properties of a class of skew-products

I. Meilijson, 1974 .

Optimal firing in sparsely-connected low-activity attractor networks

Isaac Meilijson, Eytan Ruppin, E. Ruppin, 1996, Biological Cybernetics.

Regulation of Caenorhabditis elegans body size and male tail development by the novel gene lon-8

E. Ruppin, I. Meilijson, A. Keinan, 2005, BMC Developmental Biology.

Causal Localization of Neural Function: The Shapley Value Method

Isaac Meilijson, Eytan Ruppin, Claus C. Hilgetag, 2003, Neurocomputing.

A sharp bound on the expected local time of a continuous ${\cal L}_2$-bounded Martingale

I. Meilijson, D. Gilat, L. Sacerdote, 2020, 2002.06978.

Four notions of mean-preserving increase in risk, risk attitudes and applications to the rank-dependent expected utility model

I. Meilijson, A. Chateauneuf, M. Cohen, 2004 .

The Values of Insurance Companies Under Different Uncertain Portfolios

I. Meilijson, K. Aase, 1996 .

A tale of two tails: An alternative characterization of comparative risk

I. Meilijson, M. Landsberger, 1990 .

Stochastic Orders and Stopping Times in Brownian Motion

I. Meilijson, 2003 .

Adaptive Behavior Evolution of Reinforcement Learning in Uncertain Environments: a Simple Explanation for Complex on Behalf Of: International Society of Adaptive Behavior Evolution of Reinforcement Learning in Uncertain Environments: a Simple Explanation for Complex Foraging Behaviors 2 the Model 3.

Y. Niv, D. Joel, E. Ruppin, 2022 .

Random time transformation analysis of Covid19 2020

N. Alon, I. Meilijson, 2020, medRxiv.

The time to a given drawdown in Brownian Motion

I. Meilijson, 2003 .

On the Azéma-Yor stopping time

I. Meilijson, 1983 .

There exists no ultimate solution to Skorokhod's problem

I. Meilijson, 1982 .

On the adjustment coefficient, drawdowns and Lundberg-type bounds for random walk.

I. Meilijson, 2008, 0807.3506.

Filtering With the Crowd: CrowdScreen Revisited

Isaac Meilijson, Tova Milo, Benoît Groz, 2016, ICDT.

Filtering with the Crowd: CrowdScreen revisited (technical report)

Isaac Meilijson, Tova Milo, Benoît Groz, 2018 .

Evolution of Reinforcement Learning in Uncertain Environments: Emergence of Risk-Aversion and Matching

Y. Niv, D. Joel, E. Ruppin, 2001, ECAL.

Neuronal regulation: A biologically plausible mechanism for efficient synaptic pruning in development

Isaac Meilijson, Eytan Ruppin, Gal Chechik, 1999, Neurocomputing.