Isaac Meilijson

	2011
27		Shlomi Reuveni, Isaac Meilijson, Martin Kupiec, Eytan Ruppin, Tamir Tuller: A Ribosome Flow Model for Analyzing Translation Elongation - (Extended Abstract). RECOMB 2011: 358-360
26		Tim Bedford, Isha Dewan, Isaac Meilijson, Athena Zitrou: The signal model: A model for competing risks of opportunistic maintenance. European Journal of Operational Research 214(3): 665-673 (2011)
25		Shlomi Reuveni, Isaac Meilijson, Martin Kupiec, Eytan Ruppin, Tamir Tuller: Genome-Scale Analysis of Translation Elongation with a Ribosome Flow Model. PLoS Computational Biology 7(9): (2011)
	2006
24		Alon Keinan, Ben Sandbank, Claus C. Hilgetag, Isaac Meilijson, Eytan Ruppin: Axiomatic Scalable Neurocontroller Analysis via the Shapley Value. Artificial Life 12(3): 333-352 (2006)
23		Alon Kaufman, Gideon Dror, Isaac Meilijson, Eytan Ruppin: Gene Expression of Caenorhabditis elegans Neurons Carries Information on Their Synaptic Connectivity. PLoS Computational Biology 2(12): (2006)
	2005
22		Alon Kaufman, Alon Keinan, Isaac Meilijson, Martin Kupiec, Eytan Ruppin: Quantitative Analysis of Genetic and Neuronal Multi-Perturbation Experiments. PLoS Computational Biology 1(6): (2005)
	2004
21		Alon Keinan, Ben Sandbank, Claus C. Hilgetag, Isaac Meilijson, Eytan Ruppin: Fair Attribution of Functional Contribution in Artificial and Biological Networks. Neural Computation 16(9): 1887-1915 (2004)
20		Alon Keinan, Claus C. Hilgetag, Isaac Meilijson, Eytan Ruppin: Causal localization of neural function: the Shapley value method. Neurocomputing 58-60: 215-222 (2004)
	2003
19		Lior Segev, Ranit Aharonov, Isaac Meilijson, Eytan Ruppin: High-Dimensional Analysis of Evolutionary Autonomous Agents. Artificial Life 9(1): 1-20 (2003)
18		Ranit Aharonov, Lior Segev, Isaac Meilijson, Eytan Ruppin: Localization of Function via Lesion Analysis. Neural Computation 15(4): 885-913 (2003)
	2002
17		Yael Niv, Daphna Joel, Isaac Meilijson, Eytan Ruppin: Evolution of reinforcement learning in foraging bees: a simple explanation for risk averse behavior. Neurocomputing 44-46: 951-956 (2002)
	2001
16		Ranit Aharonov, Isaac Meilijson, Eytan Ruppin: Understanding the Agent's Brain: A Quantitative Approach. ECAL 2001: 216-225
15		Yael Niv, Daphna Joel, Isaac Meilijson, Eytan Ruppin: Evolution of Reinforcement Learning in Uncertain Environments: Emergence of Risk-Aversion and Matching. ECAL 2001: 252-261
14		Gal Chechik, Isaac Meilijson, Eytan Ruppin: Effective Neuronal Learning with Ineffective Hebbian Learning Rules. Neural Computation 13(4): 817-840 (2001)
13		Nir Levy, David Horn, Isaac Meilijson, Eytan Ruppin: Distributed synchrony in a cell assembly of spiking neurons. Neural Networks 14(6-7): 815-824 (2001)
	2000
12		Ranit Aharonov-Barki, Isaac Meilijson, Eytan Ruppin: Who Does What? A Novel Algorithm to Determine Function Localization. NIPS 2000: 3-9
11		Gal Chechik, Isaac Meilijson, Eytan Ruppin: Neuronal normalization provides effective learning through ineffective synaptic learning rules. Neurocomputing 32-33: 345-351 (2000)
	1999
10		David Horn, Nir Levy, Isaac Meilijson, Eytan Ruppin: Distributed Synchrony of Spiking Neurons in a Hebbian Cell Assembly. NIPS 1999: 129-135
9		Gal Chechik, Isaac Meilijson, Eytan Ruppin: Effective Learning Requires Neuronal Remodeling of Hebbian Synapses. NIPS 1999: 96-102
8		Gal Chechik, Isaac Meilijson, Eytan Ruppin: Neuronal Regulation: A Mechanism for Synaptic Pruning During Brain Maturation. Neural Computation 11(8): 2061-2080 (1999)
7		Gal Chechik, Isaac Meilijson, Eytan Ruppin: Neuronal regulation: A biologically plausible mechanism for efficient synaptic pruning in development. Neurocomputing 26-27: 633-639 (1999)
	1998
6		Gal Chechik, Isaac Meilijson, Eytan Ruppin: Neuronal Regulation Implements Efficient Synaptic Pruning. NIPS 1998: 97-103
5		Gal Chechik, Isaac Meilijson, Eytan Ruppin: Synaptic Pruning In Development: A Computational Account. Neural Computation 10(7): 1759-1777 (1998)
	1996
4		Isaac Meilijson, Eytan Ruppin: Optimal firing in sparsely-connected low-activity attractor networks. Biological Cybernetics 74(6): 479-485 (1996)
	1993
3		Isaac Meilijson, Eytan Ruppin: Optimal Signalling in Attractor Neural Networks. NIPS 1993: 485-492
	1992
2		Isaac Meilijson, Eytan Ruppin, Moshe Sipper: Single-Iteration Threshold Hamming Networks. NIPS 1992: 564-571
1		Isaac Meilijson, Eytan Ruppin: History-Dependent Attractor Neural Networks. NIPS 1992: 572-579

Coauthor Index

1	Ranit Aharonov	[16] [18] [19]
2	Ranit Aharonov-Barki	[12]
3	Tim Bedford	[26]
4	Gal Chechik	[5] [6] [7] [8] [9] [11] [14]
5	Isha Dewan	[26]
6	Gideon Dror	[23]
7	Claus C. Hilgetag	[20] [21] [24]
8	David Horn	[10] [13]
9	Daphna Joel	[15] [17]
10	Alon Kaufman	[22] [23]
11	Alon Keinan	[20] [21] [22] [24]
12	Martin Kupiec	[22] [25] [27]
13	Nir Levy	[10] [13]
14	Yael Niv	[15] [17]
15	Shlomi Reuveni	[25] [27]
16	Eytan Ruppin	[1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23] [24] [25] [27]
17	Ben Sandbank	[21] [24]
18	Lior Segev	[18] [19]
19	Moshe Sipper	[2]
20	Tamir Tuller	[25] [27]
21	Athena Zitrou	[26]

Colors in the list of coauthors

Last update Sun Jun 3 16:06:10 2012 CET by the DBLP Team — Data released under the ODC-BY 1.0 license — See also our legal information page