Minimizing Flow Time on Parallel Identical Processors with Variable Unit Processing Time. - Isaac Meilijson; A. Tamir (Oper. Res., 1984)

The Organ Pipe Permutation. - M. Keane; Alan G. Konheim; Isaac Meilijson (SIAM J. Comput., 1984)

History-Dependent Attractor Neural Networks. - Isaac Meilijson; Eytan Ruppin (NIPS, 1992)

Single-Iteration Threshold Hamming Networks. - Isaac Meilijson; Eytan Ruppin; Moshe Sipper (NIPS, 1992)

Optimal Signalling in Attractor Neural Networks. - Isaac Meilijson; Eytan Ruppin (NIPS, 1993)

Co-monotone allocations, Bickel-Lehmann dispersion and the Arrow-Pratt measure of risk aversion. - Michael Landsberger; Isaac Meilijson (Ann. Oper. Res., 1994)

A single-iteration threshold Hamming network. - Isaac Meilijson; Eytan Ruppin; Moshe Sipper (IEEE Trans. Neural Networks, 1995)

Optimal firing in sparsely-connected low-activity attractor networks. - Isaac Meilijson; Eytan Ruppin (Biol. Cybern., 1996)

Fast computation in hamming and hopfield networks. - Isaac Meilijson; Eytan Ruppin; Moshe Sipper (Algorithms and Architectures, 1998)

Neuronal Regulation Implements Efficient Synaptic Pruning. - Gal Chechik; Isaac Meilijson; Eytan Ruppin (NIPS, 1998)

Synaptic Pruning In Development: A Computational Account. - Gal Chechik; Isaac Meilijson; Eytan Ruppin (Neural Comput., 1998)

Effective Learning Requires Neuronal Remodeling of Hebbian Synapses. - Gal Chechik; Isaac Meilijson; Eytan Ruppin (NIPS, 1999)

Distributed Synchrony of Spiking Neurons in a Hebbian Cell Assembly. - David Horn 001; Nir Levy; Isaac Meilijson; Eytan Ruppin (NIPS, 1999)

Neuronal regulation: A biologically plausible mechanism for efficient synaptic pruning in development. - Gal Chechik; Isaac Meilijson; Eytan Ruppin (Neurocomputing, 1999)

Neuronal Regulation: A Mechanism for Synaptic Pruning During Brain Maturation. - Gal Chechik; Isaac Meilijson; Eytan Ruppin (Neural Comput., 1999)

Who Does What? A Novel Algorithm to Determine Function Localization. - Ranit Aharonov-Barki; Isaac Meilijson; Eytan Ruppin (NIPS, 2000)

Neuronal normalization provides effective learning through ineffective synaptic learning rules. - Gal Chechik; Isaac Meilijson; Eytan Ruppin (Neurocomputing, 2000)

Understanding the Agent's Brain: A Quantitative Approach. - Ranit Aharonov-Barki; Isaac Meilijson; Eytan Ruppin (ECAL, 2001)

Evolution of Reinforcement Learning in Uncertain Environments: Emergence of Risk-Aversion and Matching. - Yael Niv; Daphna Joel; Isaac Meilijson; Eytan Ruppin (ECAL, 2001)

Effective Neuronal Learning with Ineffective Hebbian Learning Rules. - Gal Chechik; Isaac Meilijson; Eytan Ruppin (Neural Comput., 2001)

Distributed synchrony in a cell assembly of spiking neurons. - Nir Levy; David Horn 001; Isaac Meilijson; Eytan Ruppin (Neural Networks, 2001)

Evolution of Reinforcement Learning in Uncertain Environments: A Simple Explanation for Complex Foraging Behaviors. - Yael Niv; Daphna Joel; Isaac Meilijson; Eytan Ruppin (Adapt. Behav., 2002)

Evolution of reinforcement learning in foraging bees: a simple explanation for risk averse behavior. - Yael Niv; Daphna Joel; Isaac Meilijson; Eytan Ruppin (Neurocomputing, 2002)

High-Dimensional Analysis of Evolutionary Autonomous Agents. - Lior Segev; Ranit Aharonov-Barki; Isaac Meilijson; Eytan Ruppin (Artif. Life, 2003)

Localization of Function via Lesion Analysis. - Ranit Aharonov-Barki; Lior Segev; Isaac Meilijson; Eytan Ruppin (Neural Comput., 2003)

Linearization of local probabilistic sensitivity via sample re-weighting. - Roger M. Cooke; Dorota Kurowicka; Isaac Meilijson (Reliab. Eng. Syst. Saf., 2003)

Causal localization of neural function: the Shapley value method. - Alon Keinan; Claus C. Hilgetag; Isaac Meilijson; Eytan Ruppin (Neurocomputing, 2004)

Fair Attribution of Functional Contribution in Artificial and Biological Networks. - Alon Keinan; Ben Sandbank; Claus C. Hilgetag; Isaac Meilijson; Eytan Ruppin (Neural Comput., 2004)

Quantitative Analysis of Genetic and Neuronal Multi-Perturbation Experiments. - Alon Kaufman; Alon Keinan; Isaac Meilijson; Martin Kupiec; Eytan Ruppin (PLoS Comput. Biol., 2005)

Axiomatic Scalable Neurocontroller Analysis via the Shapley Value. - Alon Keinan; Ben Sandbank; Claus C. Hilgetag; Isaac Meilijson; Eytan Ruppin (Artif. Life, 2006)

Gene Expression of Caenorhabditis elegans Neurons Carries Information on Their Synaptic Connectivity. - Alon Kaufman; Gideon Dror; Isaac Meilijson; Eytan Ruppin (PLoS Comput. Biol., 2006)

Can single knockouts accurately single out gene functions? - David Deutscher; Isaac Meilijson; Stefan Schuster; Eytan Ruppin (BMC Syst. Biol., 2008)

A Ribosome Flow Model for Analyzing Translation Elongation - (Extended Abstract). - Shlomi Reuveni; Isaac Meilijson; Martin Kupiec; Eytan Ruppin; Tamir Tuller (RECOMB, 2011)

The signal model: A model for competing risks of opportunistic maintenance. - Tim Bedford; Isha Dewan; Isaac Meilijson; Athena Zitrou (Eur. J. Oper. Res., 2011)

Genome-Scale Analysis of Translation Elongation with a Ribosome Flow Model. - Shlomi Reuveni; Isaac Meilijson; Martin Kupiec; Eytan Ruppin; Tamir Tuller (PLoS Comput. Biol., 2011)

Filtering With the Crowd: CrowdScreen Revisited. - Benoît Groz; Ezra Levin; Isaac Meilijson; Tova Milo (ICDT, 2016)

Splitting matters: how monotone transformation of predictor variables may improve the predictions of decision tree models. - Tal Galili; Isaac Meilijson (CoRR, 2016)

Queueing with Negative Network Effects. - Refael Hassin; Isaac Meilijson; Yael Perlman (Manuf. Serv. Oper. Manag., 2023)

Dynamic history-dependent tax and environmental compliance monitoring of risk-averse firms. - Noam Goldberg; Isaac Meilijson; Yael Perlman (Ann. Oper. Res., 2024)