Scaling and Generalization in Neural Networks: A Case Study. - Subutai Ahmad; Gerald Tesauro (NIPS, 1988)

A study of scaling and generalization in neural networks. - Subutai Ahmad; Gerald Tesauro (Neural Networks, 1988)

Asymptotic Convergence of Backpropagation: Numerical Experiments. - Subutai Ahmad; Gerald Tesauro; Yu He (NIPS, 1989)

Asymptotic Convergence of Backpropagation. - Gerald Tesauro; Yu He; Subutai Ahmad (Neural Comput., 1989)

VISIT: A Neural Model of Covert Visual Attention. - Subutai Ahmad (NIPS, 1991)

VISIT: An efficient computational model of human visual attention - Subutai Ahmad (1991)

Some Solutions to the Missing Feature Problem in Vision. - Subutai Ahmad; Volker Tresp (NIPS, 1992)

Network Structuring and Training Using Rule-Based Knowledge. - Volker Tresp; Jürgen Hollatz; Subutai Ahmad (NIPS, 1992)

Classification with missing and uncertain inputs. - Subutai Ahmad; Volker Tresp (ICNN, 1993)

Feature Densities Are Required for Computing Feature Correspondences. - Subutai Ahmad (NIPS, 1993)

Training Neural Networks with Deficient Data. - Volker Tresp; Subutai Ahmad; Ralph Neuneier (NIPS, 1993)

David Touretzky, Jeffrey Elman, Terrence Sejnowski and Geoffrey Hinton, eds., Connectionist Models: Proceedings of the 1990 Summer School. - Subutai Ahmad (Artif. Intell., 1993)

Efficient Methods for Dealing with Missing Data in Supervised Learning. - Volker Tresp; Ralph Neuneier; Subutai Ahmad (NIPS, 1994)

Representing Probabilistic Rules with Networks of Gaussian Basis Functions. - Volker Tresp; Jürgen Hollatz; Subutai Ahmad (Mach. Learn., 1997)

Analysis-by-synthesis dissolve detection. - Michele Covell; Subutai Ahmad (ICIP (2), 2002)

Automated machine learning for autonomic computing. - Subutai Ahmad (ICAC, 2012)

Evaluating Real-Time Anomaly Detection Algorithms - The Numenta Anomaly Benchmark. - Alexander Lavin; Subutai Ahmad (ICMLA, 2015)

Properties of Sparse Distributed Representations and their Application to Hierarchical Temporal Memory. - Subutai Ahmad; Jeff Hawkins (CoRR, 2015)

Porting HTM Models to the Heidelberg Neuromorphic Computing Platform. - Sebastian Billaudelle; Subutai Ahmad (CoRR, 2015)

Continuous online sequence learning with an unsupervised neural network model. - Yuwei Cui; Chetan Surpur; Subutai Ahmad; Jeff Hawkins (CoRR, 2015)

Why Neurons Have Thousands of Synapses, A Theory of Sequence Memory in Neocortex. - Jeff Hawkins; Subutai Ahmad (CoRR, 2015)

A comparative study of HTM and other neural network models for online sequence learning with streaming data. - Yuwei Cui; Chetan Surpur; Subutai Ahmad; Jeff Hawkins (IJCNN, 2016)

How do neurons operate on sparse distributed representations? A mathematical theory of sparsity, neurons and active dendrites. - Subutai Ahmad; Jeff Hawkins (CoRR, 2016)

Real-Time Anomaly Detection for Streaming Analytics. - Subutai Ahmad; Scott Purdy (CoRR, 2016)

Continuous Online Sequence Learning with an Unsupervised Neural Network Model. - Yuwei Cui; Subutai Ahmad; Jeff Hawkins (Neural Comput., 2016)

The HTM Spatial Pooler - A Neocortical Algorithm for Online Sparse Distributed Coding. - Yuwei Cui; Subutai Ahmad; Jeff Hawkins (Frontiers Comput. Neurosci., 2017)

Unsupervised real-time anomaly detection for streaming data. - Subutai Ahmad; Alexander Lavin; Scott Purdy; Zuha Agha (Neurocomputing, 2017)

A Sequence-Based Neuronal Model for Mobile Robot Localization. - Peer Neubert; Subutai Ahmad; Peter Protzel (KI, 2018)

Biologically Driven Artificial Intelligence. - Kjell Jørgen Hole; Subutai Ahmad (Computer, 2019)

How Can We Be So Dense? The Benefits of Using Highly Sparse Representations. - Subutai Ahmad; Luiz Scheinkman (CoRR, 2019)

Long Distance Relationships Without Time Travel: Boosting the Performance of a Sparse Predictive Autoencoder in Sequence Modeling. - Jeremy Gordon 001; David Rawlinson 001; Subutai Ahmad (ANNPR, 2020)

Grid Cell Path Integration For Movement-Based Visual Object Recognition. - Niels Leadholm; Marcus Lewis; Subutai Ahmad (BMVC, 2021)

Avalanche: An End-to-End Library for Continual Learning. - Vincenzo Lomonaco; Lorenzo Pellegrini; Andrea Cossu; Antonio Carta; Gabriele Graffieti; Tyler L. Hayes; Matthias De Lange; Marc Masana; Jary Pomponi; Gido M. van de Ven; Martin Mundt; Qi She; et al. (CVPR Workshops, 2021)

Avoiding Catastrophe: Active Dendrites Enable Multi-Task Learning in Dynamic Environments. - Abhiram Iyer; Karan Grewal; Akash Velu; Lucas Oliveira Souza; Jeremy Forest; Subutai Ahmad (Frontiers Neurorobotics, 2022)

Two sparsities are better than one: unlocking the performance benefits of sparse-sparse networks. - Kevin Lee Hunter; Lawrence Spracklen; Subutai Ahmad (Neuromorph. Comput. Eng., 2022)

Supercharged AI Inference on Modern CPUs. - Lawrence Spracklen; Subutai Ahmad (HCS, 2023)