Subutai Ahmad

Proceedings of the 35th IEEE Hot Chips Symposium, 2023

2022

Two sparsities are better than one: unlocking the performance benefits of sparse-sparse networks.

[BibT_eX]

[DOI]

Kevin Lee Hunter

Lawrence Spracklen

Neuromorph. Comput. Eng., 2022

Avoiding Catastrophe: Active Dendrites Enable Multi-Task Learning in Dynamic Environments.

[BibT_eX]

[DOI]

Frontiers Neurorobotics, 2022

2021

Avalanche: An End-to-End Library for Continual Learning.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

Grid Cell Path Integration For Movement-Based Visual Object Recognition.

[BibT_eX]

[DOI]

Niels Leadholm

Marcus Lewis

Proceedings of the 32nd British Machine Vision Conference 2021, 2021

2020

Long Distance Relationships Without Time Travel: Boosting the Performance of a Sparse Predictive Autoencoder in Sequence Modeling.

[BibT_eX]

[DOI]

Jeremy Gordon

David Rawlinson

Proceedings of the Artificial Neural Networks in Pattern Recognition, 2020

2019

How Can We Be So Dense? The Benefits of Using Highly Sparse Representations.

[BibT_eX]

[DOI]

Luiz Scheinkman

CoRR, 2019

Biologically Driven Artificial Intelligence.

[BibT_eX]

[DOI]

Kjell Jørgen Hole

Computer, 2019

2018

A Sequence-Based Neuronal Model for Mobile Robot Localization.

[BibT_eX]

[DOI]

Peer Neubert

Peter Protzel

Proceedings of the KI 2018: Advances in Artificial Intelligence, 2018

2017

Unsupervised real-time anomaly detection for streaming data.

[BibT_eX]

[DOI]

Neurocomputing, 2017

The HTM Spatial Pooler - A Neocortical Algorithm for Online Sparse Distributed Coding.

[BibT_eX]

[DOI]

Yuwei Cui

Frontiers Comput. Neurosci., 2017

2016

Continuous Online Sequence Learning with an Unsupervised Neural Network Model.

[BibT_eX]

[DOI]

Yuwei Cui

Neural Comput., 2016

Real-Time Anomaly Detection for Streaming Analytics.

[BibT_eX]

[DOI]

Scott Purdy

CoRR, 2016

How do neurons operate on sparse distributed representations? A mathematical theory of sparsity, neurons and active dendrites.

[BibT_eX]

[DOI]

CoRR, 2016

A comparative study of HTM and other neural network models for online sequence learning with streaming data.

[BibT_eX]

[DOI]

Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

2015

Why Neurons Have Thousands of Synapses, A Theory of Sequence Memory in Neocortex.

[BibT_eX]

[DOI]

CoRR, 2015

Continuous online sequence learning with an unsupervised neural network model.

[BibT_eX]

[DOI]

CoRR, 2015

Porting HTM Models to the Heidelberg Neuromorphic Computing Platform.

[BibT_eX]

[DOI]

Sebastian Billaudelle

CoRR, 2015

Properties of Sparse Distributed Representations and their Application to Hierarchical Temporal Memory.

[BibT_eX]

[DOI]

CoRR, 2015

Evaluating Real-Time Anomaly Detection Algorithms - The Numenta Anomaly Benchmark.

[BibT_eX]

[DOI]

Alexander Lavin

Proceedings of the 14th IEEE International Conference on Machine Learning and Applications, 2015

2012

Automated machine learning for autonomic computing.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Autonomic Computing, 2012

2002

Analysis-by-synthesis dissolve detection.

[BibT_eX]

[DOI]

Michele Covell

Proceedings of the 2002 International Conference on Image Processing, 2002

1997

Representing Probabilistic Rules with Networks of Gaussian Basis Functions.

[BibT_eX]

[DOI]

Jürgen Hollatz

Mach. Learn., 1997

1994

Efficient Methods for Dealing with Missing Data in Supervised Learning.

[BibT_eX]

[DOI]

Ralph Neuneier

Proceedings of the Advances in Neural Information Processing Systems 7, 1994

1993

David Touretzky, Jeffrey Elman, Terrence Sejnowski and Geoffrey Hinton, eds., Connectionist Models: Proceedings of the 1990 Summer School.

[BibT_eX]

Artif. Intell., 1993

Training Neural Networks with Deficient Data.

[BibT_eX]

[DOI]

Ralph Neuneier

Proceedings of the Advances in Neural Information Processing Systems 6, 1993

Feature Densities Are Required for Computing Feature Correspondences.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 6, 1993

Classification with missing and uncertain inputs.

[BibT_eX]

[DOI]

Proceedings of International Conference on Neural Networks (ICNN'88), San Francisco, CA, USA, March 28, 1993

1992

Network Structuring and Training Using Rule-Based Knowledge.

[BibT_eX]

[DOI]

Jürgen Hollatz

Proceedings of the Advances in Neural Information Processing Systems 5, [NIPS Conference, Denver, Colorado, USA, November 30, 1992

Some Solutions to the Missing Feature Problem in Vision.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 5, [NIPS Conference, Denver, Colorado, USA, November 30, 1992

1991

VISIT: An efficient computational model of human visual attention

[BibT_eX]

[DOI]

PhD thesis, 1991

VISIT: A Neural Model of Covert Visual Attention.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 4, 1991

1989

Asymptotic Convergence of Backpropagation.

[BibT_eX]

[DOI]

Yu He

Neural Comput., 1989

Asymptotic Convergence of Backpropagation: Numerical Experiments.

[BibT_eX]

[DOI]

Yu He

Proceedings of the Advances in Neural Information Processing Systems 2, 1989

1988

A study of scaling and generalization in neural networks.

[BibT_eX]

[DOI]

Neural Networks, 1988

Scaling and Generalization in Neural Networks: A Case Study.

[BibT_eX]

[DOI]