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Subutai Ahmad
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2020 – today
- 2023
- [c18]Lawrence Spracklen, Subutai Ahmad:
Supercharged AI Inference on Modern CPUs. HCS 2023: 1-21 - 2022
- [j10]Abhiram Iyer, Karan Grewal, Akash Velu, Lucas Oliveira Souza, Jeremy Forest, Subutai Ahmad
:
Avoiding Catastrophe: Active Dendrites Enable Multi-Task Learning in Dynamic Environments. Frontiers Neurorobotics 16: 846219 (2022) - [j9]Kevin Lee Hunter, Lawrence Spracklen, Subutai Ahmad
Two sparsities are better than one: unlocking the performance benefits of sparse-sparse networks. Neuromorph. Comput. Eng. 2(3): 34004 (2022) - [i12]Abhiram Iyer, Karan Grewal, Akash Velu, Lucas Oliveira Souza, Jeremy Forest, Subutai Ahmad:
Avoiding Catastrophe: Active Dendrites Enable Multi-Task Learning in Dynamic Environments. CoRR abs/2201.00042 (2022) - 2021
- [c17]Niels Leadholm, Marcus Lewis, Subutai Ahmad:
Grid Cell Path Integration For Movement-Based Visual Object Recognition. BMVC 2021: 118 - [c16]Vincenzo Lomonaco
Avalanche: An End-to-End Library for Continual Learning. CVPR Workshops 2021: 3600-3610 - [i11]Niels Leadholm, Marcus Lewis, Subutai Ahmad:
Grid Cell Path Integration For Movement-Based Visual Object Recognition. CoRR abs/2102.09076 (2021) - [i10]Kevin Lee Hunter, Lawrence Spracklen, Subutai Ahmad:
Two Sparsities Are Better Than One: Unlocking the Performance Benefits of Sparse-Sparse Networks. CoRR abs/2112.13896 (2021) - 2020
- [c15]Jeremy Gordon
Long Distance Relationships Without Time Travel: Boosting the Performance of a Sparse Predictive Autoencoder in Sequence Modeling. ANNPR 2020: 52-64
2010 – 2019
- 2019
- [j8]Kjell Jørgen Hole
Biologically Driven Artificial Intelligence. Computer 52(8): 72-75 (2019) - [i9]Subutai Ahmad, Luiz Scheinkman:
How Can We Be So Dense? The Benefits of Using Highly Sparse Representations. CoRR abs/1903.11257 (2019) - [i8]Jeremy Gordon, David Rawlinson, Subutai Ahmad:
Long Distance Relationships without Time Travel: Boosting the Performance of a Sparse Predictive Autoencoder in Sequence Modeling. CoRR abs/1912.01116 (2019) - 2018
- [c14]Peer Neubert, Subutai Ahmad, Peter Protzel:
A Sequence-Based Neuronal Model for Mobile Robot Localization. KI 2018: 117-130 - 2017
- [j7]Yuwei Cui, Subutai Ahmad, Jeff Hawkins:
The HTM Spatial Pooler - A Neocortical Algorithm for Online Sparse Distributed Coding. Frontiers Comput. Neurosci. 11: 111 (2017) - [j6]Subutai Ahmad
Unsupervised real-time anomaly detection for streaming data. Neurocomputing 262: 134-147 (2017) - 2016
- [j5]Yuwei Cui, Subutai Ahmad
Continuous Online Sequence Learning with an Unsupervised Neural Network Model. Neural Comput. 28(11): 2474-2504 (2016) - [c13]Yuwei Cui, Chetan Surpur, Subutai Ahmad
A comparative study of HTM and other neural network models for online sequence learning with streaming data. IJCNN 2016: 1530-1538 - [i7]Subutai Ahmad, Jeff Hawkins:
How do neurons operate on sparse distributed representations? A mathematical theory of sparsity, neurons and active dendrites. CoRR abs/1601.00720 (2016) - [i6]Subutai Ahmad, Scott Purdy:
Real-Time Anomaly Detection for Streaming Analytics. CoRR abs/1607.02480 (2016) - 2015
- [c12]Alexander Lavin
Evaluating Real-Time Anomaly Detection Algorithms - The Numenta Anomaly Benchmark. ICMLA 2015: 38-44 - [i5]Subutai Ahmad, Jeff Hawkins:
Properties of Sparse Distributed Representations and their Application to Hierarchical Temporal Memory. CoRR abs/1503.07469 (2015) - [i4]Sebastian Billaudelle, Subutai Ahmad:
Porting HTM Models to the Heidelberg Neuromorphic Computing Platform. CoRR abs/1505.02142 (2015) - [i3]Alexander Lavin, Subutai Ahmad:
Evaluating Real-time Anomaly Detection Algorithms - the Numenta Anomaly Benchmark. CoRR abs/1510.03336 (2015) - [i2]Jeff Hawkins, Subutai Ahmad:
Why Neurons Have Thousands of Synapses, A Theory of Sequence Memory in Neocortex. CoRR abs/1511.00083 (2015) - [i1]Yuwei Cui, Chetan Surpur, Subutai Ahmad, Jeff Hawkins:
Continuous online sequence learning with an unsupervised neural network model. CoRR abs/1512.05463 (2015) - 2012
- [c11]Subutai Ahmad:
Automated machine learning for autonomic computing. ICAC 2012: 103-104
2000 – 2009
- 2002
- [c10]Michele Covell, Subutai Ahmad:
Analysis-by-synthesis dissolve detection. ICIP (2) 2002: 425-428
1990 – 1999
- 1997
- [j4]Volker Tresp, Jürgen Hollatz, Subutai Ahmad:
Representing Probabilistic Rules with Networks of Gaussian Basis Functions. Mach. Learn. 27(2): 173-200 (1997) - 1994
- [c9]Volker Tresp, Ralph Neuneier, Subutai Ahmad:
Efficient Methods for Dealing with Missing Data in Supervised Learning. NIPS 1994: 689-696 - 1993
- [j3]Subutai Ahmad:
David Touretzky, Jeffrey Elman, Terrence Sejnowski and Geoffrey Hinton, eds., Connectionist Models: Proceedings of the 1990 Summer School. Artif. Intell. 62(1): 117-127 (1993) - [c8]Subutai Ahmad, Volker Tresp:
Classification with missing and uncertain inputs. ICNN 1993: 1949-1954 - [c7]Volker Tresp, Subutai Ahmad, Ralph Neuneier:
Training Neural Networks with Deficient Data. NIPS 1993: 128-135 - [c6]Subutai Ahmad:
Feature Densities Are Required for Computing Feature Correspondences. NIPS 1993: 961-968 - 1992
- [c5]Subutai Ahmad, Volker Tresp:
Some Solutions to the Missing Feature Problem in Vision. NIPS 1992: 393-400 - [c4]Volker Tresp, Jürgen Hollatz, Subutai Ahmad:
Network Structuring and Training Using Rule-Based Knowledge. NIPS 1992: 871-878 - 1991
- [b1]Subutai Ahmad:
VISIT: An efficient computational model of human visual attention. University of Illinois Urbana-Champaign, USA, 1991 - [c3]Subutai Ahmad:
VISIT: A Neural Model of Covert Visual Attention. NIPS 1991: 420-427
1980 – 1989
- 1989
- [j2]Gerald Tesauro, Yu He, Subutai Ahmad
Asymptotic Convergence of Backpropagation. Neural Comput. 1(3): 382-391 (1989) - [c2]Subutai Ahmad, Gerald Tesauro, Yu He:
Asymptotic Convergence of Backpropagation: Numerical Experiments. NIPS 1989: 606-613 - 1988
- [j1]Subutai Ahmad, Gerald Tesauro:
A study of scaling and generalization in neural networks. Neural Networks 1(Supplement-1): 3-6 (1988) - [c1]Subutai Ahmad, Gerald Tesauro:
Scaling and Generalization in Neural Networks: A Case Study. NIPS 1988: 160-168
Coauthor Index
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