Xiangbao Wu

17 papers Journal 16Unranked 1
YearRankTypeTitle / Venue / Authors
2006 J jnl
Decision functions that can support a hippocampal model.
Neurocomputing
Xiangbao Wu, William B. Levy
2006 J jnl
Erratum to: Interpreting hippocampal function as recoding and forecasting [Neural Networks 18 (9) 1242-1264].
Neural Networks
William B. Levy, Ashlie B. Hocking, Xiangbao Wu
2006 J jnl
External activity and the freedom to recode.
Neurocomputing
William B. Levy, Xiangbao Wu
2005 J jnl
Erratum to 'Increasing CS and US longevity increases the learnable trace interval' by X. Wu and W.B. Levy: [Neurocomputing 65-66 (2005) 283-289].
Neurocomputing
Xiangbao Wu, William B. Levy
2005 J jnl
Increasing CS and US longevity increases the learnable trace interval.
Neurocomputing
Xiangbao Wu, William B. Levy
2005 J jnl
Interpreting hippocampal function as recoding and forecasting.
Neural Networks
William B. Levy, Ashlie B. Hocking, Xiangbao Wu
2005 J jnl
The formation of neural codes in the hippocampus: trace conditioning as a prototypical paradigm for studying the random recoding hypothesis.
Biol. Cybern.
William B. Levy, A. Sanyal, Xiangbao Wu, Paul Rodríguez, David W. Sullivan
2003 J jnl
A source of individual variation.
Neurocomputing
William B. Levy, Xiangbao Wu, Anthony J. Greene, Barbara A. Spellman
2002 J jnl
Simulating the transverse non-patterning problem.
Neurocomputing
Xiangbao Wu, William B. Levy
2001 J jnl
Simulating symbolic distance effects in the transitive inference problem.
Neurocomputing
Xiangbao Wu, William B. Levy
2000 J jnl
Entorhinal/dentate excitation of CA3: A critical variable in hippocampal models.
Neurocomputing
Sean Polyn, Xiangbao Wu, William B. Levy
2000 J jnl
Using computational simulations to discover optimal training paradigms.
Neurocomputing
Aaron P. Shon, Xiangbao Wu, William B. Levy
1999 J jnl
Enhancing the performance of a hippocampal model by increasing variability early in learning.
Neurocomputing
Xiangbao Wu, William B. Levy
1998 J jnl
A neural network solution to the transverse patterning problem depends on repetition of the input code.
Biol. Cybern.
Xiangbao Wu, Joanna Tyrcha, William B. Levy
1997 — conf
A simple, biologically motivated neural network solves the transitive inference problem.
ICNN
William B. Levy, Xiangbao Wu
1996 J jnl
Context codes and the effect of noisy learning on a simplified hippocampal CA3 model.
Biol. Cybern.
Xiangbao Wu, Robert A. Baxter, William B. Levy
1995 J jnl
Noise-enhanced performance in a cortical associative memory model.
Int. J. Neural Syst.
Hans Liljenström, Xiangbao Wu