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← Core Methods
Machine Learning
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Core Methods
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Neural Networks
78 directly classified papers
Papers per year
2006: 1
2007: 2
2008: 2
2009: 2
2010: 1
2011: 5
2012: 4
2013: 3
2014: 2
2016: 1
2017: 1
2018: 2
2019: 4
2020: 9
2021: 5
2022: 8
2023: 7
2024: 12
2025: 7
Papers
Towards Improving Neural Named Entity Recognition with Gazetteers
ACL 2019
Computer Assisted Annotation of Tension Development in TED Talks through Crowdsourcing
EMNLP 2019
Simplified Abugidas
ACL 2018
Neural Guided Constraint Logic Programming for Program Synthesis
NIPS 2018
Global Optimality in Neural Network Training
CVPR 2017
Toward Deeper Understanding of Neural Networks: The Power of Initialization and a Dual View on Expressivity
NIPS 2016
Analog Memories in a Balanced Rate-Based Network of E-I Neurons
NIPS 2014
Spike Frequency Adaptation Implements Anticipative Tracking in Continuous Attractor Neural Networks
NIPS 2014
Firing rate predictions in optimal balanced networks
NIPS 2013
Recurrent networks of coupled Winner-Take-All oscillators for solving constraint satisfaction problems
NIPS 2013
Capacity of strong attractor patterns to model behavioural and cognitive prototypes
NIPS 2013
Multi-scale Hyper-time Hardware Emulation of Human Motor Nervous System Based on Spiking Neurons using FPGA
NIPS 2012
Delay Compensation with Dynamical Synapses
NIPS 2012
Spiking and saturating dendrites differentially expand single neuron computation capacity
NIPS 2012
Analog readout for optical reservoir computers
NIPS 2012
Shallow vs. Deep Sum-Product Networks
NIPS 2011
Active dendrites: adaptation to spike-based communication
NIPS 2011
Variational Learning for Recurrent Spiking Networks
NIPS 2011
A Brain-Machine Interface Operating with a Real-Time Spiking Neural Network Control Algorithm
NIPS 2011
Emergence of Multiplication in a Biophysical Model of a Wide-Field Visual Neuron for Computing Object Approaches: Dynamics, Peaks, & Fits
NIPS 2011
Over-complete representations on recurrent neural networks can support persistent percepts
NIPS 2010
Replacing supervised classification learning by Slow Feature Analysis in spiking neural networks
NIPS 2009
Code-specific policy gradient rules for spiking neurons
NIPS 2009
On Computational Power and the Order-Chaos Phase Transition in Reservoir Computing
NIPS 2008
Tracking Changing Stimuli in Continuous Attractor Neural Networks
NIPS 2008
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