L. F. Abbott - RankMe

53 papers A* 1B 1Journal 45Unranked 6

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Emergent neural dynamics and geometry for generalization in a transitive inference task. PLoS Comput. Biol. Kenneth Kay, Natalie Biderman, Ramin Khajeh, Manuel Beiran, Christopher J. Cueva, Daphna Shohamy, Greg Jensen, Xue-Xin Wei, Vincent P. Ferrera, L. F. Abbott
2023	J	`jnl`	Theory of coupled neuronal-synaptic dynamics. CoRR David G. Clark, L. F. Abbott
2022	J	`jnl`	Dimension of Activity in Random Neural Networks. CoRR David G. Clark, L. F. Abbott, Ashok Litwin-Kumar
2022	J	`jnl`	Input correlations impede suppression of chaos and learning in balanced firing-rate networks. PLoS Comput. Biol. Rainer Engelken, Alessandro Ingrosso, Ramin Khajeh, Sven Goedeke, L. F. Abbott
2022	J	`jnl`	Input correlations impede suppression of chaos and learning in balanced rate networks. CoRR Rainer Engelken, Alessandro Ingrosso, Ramin Khajeh, Sven Goedeke, L. F. Abbott
2022	J	`jnl`	Sparse RNNs can support high-capacity classification. PLoS Comput. Biol. Denis Turcu, L. F. Abbott
2022	J	`jnl`	Sparse balance: Excitatory-inhibitory networks with small bias currents and broadly distributed synaptic weights. PLoS Comput. Biol. Ramin Khajeh, Francesco Fumarola, L. F. Abbott
2022	J	`jnl`	The Implicit Bias of Gradient Descent on Generalized Gated Linear Networks. CoRR Samuel Lippl, L. F. Abbott, SueYeon Chung
2021	A*	`conf`	Credit Assignment Through Broadcasting a Global Error Vector. NeurIPS David G. Clark, L. F. Abbott, SueYeon Chung
2021	J	`jnl`	Credit Assignment Through Broadcasting a Global Error Vector. CoRR David G. Clark, L. F. Abbott, SueYeon Chung
2021	J	`jnl`	Neural population geometry: An approach for understanding biological and artificial neural networks. CoRR SueYeon Chung, L. F. Abbott
2018	J	`jnl`	Feedback alignment in deep convolutional networks. CoRR Theodore H. Moskovitz, Ashok Litwin-Kumar, L. F. Abbott
2018	J	`jnl`	Training dynamically balanced excitatory-inhibitory networks. CoRR Alessandro Ingrosso, L. F. Abbott
2017	J	`jnl`	Balanced Excitation and Inhibition are Required for High-Capacity, Noise-Robust Neuronal Selectivity. CoRR Ran Rubin, L. F. Abbott, Haim Sompolinsky
2017	J	`jnl`	full-FORCE: A Target-Based Method for Training Recurrent Networks. CoRR Brian DePasquale, Christopher J. Cueva, Kanaka Rajan, G. Sean Escola, L. F. Abbott
2016	J	`jnl`	LFADS - Latent Factor Analysis via Dynamical Systems. CoRR David Sussillo, Rafal Józefowicz, L. F. Abbott, Chethan Pandarinath
2016	J	`jnl`	Stability and Competition in Multi-spike Models of Spike-Timing Dependent Plasticity. PLoS Comput. Biol. Baktash Babadi, L. F. Abbott
2016	J	`jnl`	Tuning Curves for Arm Posture Control in Motor Cortex Are Consistent with Random Connectivity. PLoS Comput. Biol. Hagai Lalazar, L. F. Abbott, Eilon Vaadia
2014	J	`jnl`	Hierarchical Control Using Networks Trained with Higher-Level Forward Models. Neural Comput. Greg Wayne, L. F. Abbott
2013	J	`jnl`	A Complex-Valued Firing-Rate Model That Approximates the Dynamics of Spiking Networks. PLoS Comput. Biol. Evan S. Schaffer, Srdjan Ostojic, L. F. Abbott
2013	J	`jnl`	Pairwise Analysis Can Account for Network Structures Arising from Spike-Timing Dependent Plasticity. PLoS Comput. Biol. Baktash Babadi, L. F. Abbott
2010	—	`conf`	Inferring Stimulus Selectivity from the Spatial Structure of Neural Network Dynamics. NIPS Kanaka Rajan, L. F. Abbott, Haim Sompolinsky
2010	J	`jnl`	Intrinsic Stability of Temporally Shifted Spike-Timing Dependent Plasticity. PLoS Comput. Biol. Baktash Babadi, L. F. Abbott
2008	J	`jnl`	Mechanism of gain modulation at single neuron and network levels. J. Comput. Neurosci. Marina Brozovic, L. F. Abbott, Richard A. Andersen
2005	J	`jnl`	Supervised Learning Through Neuronal Response Modulation. Neural Comput. Christian D. Swinehart, L. F. Abbott
2004	J	`jnl`	Control of network activity through neuronal response modulation. Neurocomputing Christian D. Swinehart, Kris Bouchard, Peretz Partensky, L. F. Abbott
2004	J	`jnl`	Synaptic equalization by anti-STDP. Neurocomputing Clifton C. Rumsey, L. F. Abbott
2002	J	`jnl`	Modeling temporal combination selective neurons of the songbird. Neurocomputing Patrick J. Drew, L. F. Abbott
2001	J	`jnl`	Input-specific adaptation in complex cells through synaptic depression. Neurocomputing Frances S. Chance, L. F. Abbott
2000	J	`jnl`	A recurrent network model for the phase invariance of complex cell responses. Neurocomputing Frances S. Chance, Sacha B. Nelson, L. F. Abbott
2000	J	`jnl`	Dependence of firing pattern on intrinsic ionic conductances: Sensitive and insensitive combinations. Neurocomputing Mark S. Goldman, Jorge Golowasch, Eve Marder, L. F. Abbott
2000	J	`jnl`	Do Simple Cells in Primary Visual Cortex Form a Tight Frame? Neural Comput. Emilio Salinas, L. F. Abbott
2000	J	`jnl`	Gain modulation of recurrent networks. Neurocomputing Jian Zhang, L. F. Abbott
2000	J	`jnl`	Temporally asymmetric Hebbian learning and neuronal response variability. Neurocomputing Sen Song, L. F. Abbott
1999	J	`jnl`	Decorrelation of spike trains by synaptic depression. Neurocomputing Mark S. Goldman, Sacha B. Nelson, L. F. Abbott
1999	J	`jnl`	Network Stability from Activity-Dependent Regulation of Neuronal Conductances. Neural Comput. Jorge Golowasch, Michael Casey, L. F. Abbott, Eve Marder
1999	—	`conf`	Self-Assembly of Oscillatory Neurons and Networks. IWANN (1) Eve Marder, Jorge Golowasch, Kathryn S. Richards, Cristina Soto-Treviño, William L. Miller, L. F. Abbott
1999	J	`jnl`	The Effect of Correlated Variability on the Accuracy of a Population Code. Neural Comput. L. F. Abbott, Peter Dayan
1998	—	`conf`	Recurrent Cortical Amplification Produces Complex Cell Responses. NIPS Frances S. Chance, Sacha B. Nelson, L. F. Abbott
1998	—	`conf`	Temporally Asymmetric Hebbian Learning, Spike liming and Neural Response Variability. NIPS L. F. Abbott, Sen Song
1997	J	`jnl`	Learning Navigational Maps Through Potentiation and Modulation of Hippocampal Place Cells. J. Comput. Neurosci. Wulfram Gerstner, L. F. Abbott
1996	J	`jnl`	A model of spatial map formation in the hippocampus of the rat. Neural Comput. K. I. Blum, L. F. Abbott
1995	J	`jnl`	Reduced Representation by Neural Networks with Restricted Receptive Fields. Neural Comput. Marco Idiart, Barry Berk, L. F. Abbott
1994	J	`jnl`	Vector reconstruction from firing rates. J. Comput. Neurosci. Emilio Salinas, L. F. Abbott
1994	J	`jnl`	When inhibition not excitation synchronizes neural firing. J. Comput. Neurosci. Carl Vreeswijk, L. F. Abbott, G. Bard Ermentrout
1993	J	`jnl`	Analysis of Neuron Models with Dynamically Regulated Conductances. Neural Comput. L. F. Abbott, Gwendal Le Masson
1993	J	`jnl`	Self-Sustained Firing in Populations of Integrate-and-Fire Neurons. SIAM J. Appl. Math. Carl Vanvreeswijk, L. F. Abbott
1992	—	`conf`	Hybrid Circuits of Interacting Computer Model and Biological Neurons. NIPS Sylvie Renaud-Le Masson, Gwendal Le Masson, Eve Marder, L. F. Abbott
1992	J	`jnl`	Reduction of conductance-based neuron models. Biol. Cybern. Thomas B. Kepler, L. F. Abbott, Eve Marder
1991	J	`jnl`	Oscillating Networks: Control of Burst Duration by Electrically Coupled Neurons. Neural Comput. L. F. Abbott, Eve Marder, Scott L. Hooper
1991	J	`jnl`	The path integral for dendritic trees. Biol. Cybern. L. F. Abbott, Edward Farhi, Sam Gutmann
1990	—	`conf`	Order Reduction for Dynamical Systems Describing the Behavior of Complex Neurons. NIPS Thomas B. Kepler, L. F. Abbott, Eve Marder
1990	B	`conf`	Oscillating networks: modeling the pyloric circuit of the stomatogastric ganglion. IJCNN L. F. Abbott, Scott L. Hooper, Thomas B. Kepler, Eve Marder