A neural network model for invariant pattern recognition. - Narayan Srinivasa; Musa K. Jouaneh (IEEE Trans. Signal Process., 1992)

An invariant pattern recognition machine using a modified ART architecture. - Narayan Srinivasa; Musa K. Jouaneh (IEEE Trans. Syst. Man Cybern., 1993)

A framework for robot control with active vision using a neural network based spatial representation. - Rajeev Sharma; Narayan Srinivasa (ICRA, 1996)

On planning immobilizing grasps for a reconfigurable gripper. - Attawith Sudsang; Narayan Srinivasa; Jean Ponce (IROS, 1997)

Grasping and in-hand manipulation: experiments with a reconfigurable gripper. - Attawith Sudsang; Jean Ponce; Narayan Srinivasa (Adv. Robotics, 1997)

SOIM: a self-organizing invertible map with applications in active vision. - Narayan Srinivasa; Rajeev Sharma (IEEE Trans. Neural Networks, 1997)

Learning and generalization of noisy mappings using a modified PROBART neural network. - Narayan Srinivasa (IEEE Trans. Signal Process., 1997)

Learning Multiscale Image Models of 2D Object Classes. - Benoit Perrin; Narendra Ahuja; Narayan Srinivasa (ACCV (2), 1998)

A Learning Approach to Fixating on 3D Targets with Active Cameras. - Narayan Srinivasa; Narendra Ahuja (ACCV (1), 1998)

Efficient Learning of VAM-Based Representation of 3D Targets and its Active Vision Applications. - Narayan Srinivasa; Rajeev Sharma (Neural Networks, 1998)

A framework for active vision-based robot control using neural networks. - Rajeev Sharma; Narayan Srinivasa (Robotica, 1998)

A topological and temporal correlator network for spatiotemporal pattern learning, recognition, and recall. - Narayan Srinivasa; Narendra Ahuja (IEEE Trans. Neural Networks, 1999)

An On-line Method for Self Organized Learningn and Extraction of Fuzzy From High Dimensional Data. - Swarup Medasani; Narayan Srinivasa; Yuri Owechko (FUZZ-IEEE, 2001)

Fuzzy edge-symmetry features for improved intruder detection. - Narayan Srinivasa; Swarup Medasani; Yuri Owechko; Deepak Khosla (FUZZ-IEEE, 2003)

Classifier Swarms for Human Detection in Infrared Imagery. - Yuri Owechko; Swarup Medasani; Narayan Srinivasa (CVPR Workshops, 2004)

Active fuzzy clustering for collaborative filtering. - Narayan Srinivasa; Swarup Medasani (FUZZ-IEEE, 2004)

Active learning system for object fingerprinting. - Swarup Medasani; Narayan Srinivasa; Yuri Owechko (IJCNN, 2004)

Modeling of pedestrian motion for recognition. - Payam Saisan; Swarup Medasani; Narayan Srinivasa; Yuri Owechko (Electronic Imaging: Image and Video Communications and Processing, 2005)

A Self-Organizing Neural Model for Fault-Tolerant Control of Redundant Robots. - Narayan Srinivasa; Stephen Grossberg (IJCNN, 2007)

Bio-Inspired Planning and Reaching in Complex Environments. - Rajan Bhattacharyya; Narayan Srinivasa; Stephen Grossberg (AAAI Fall Symposium: Biologically Inspired Cognitive Architectures, 2008)

Learning Invariant Sensory-Motor Transforms for Fault-Tolerant Control of Redundant Robots. - Narayan Srinivasa; Stephen Grossberg (AAAI Fall Symposium: Biologically Inspired Cognitive Architectures, 2008)

High-Impact Event Prediction by Temporal Data Mining through Genetic Algorithms. - Narayan Srinivasa; Qin Jiang; Leandro G. Barajas (ICNC (1), 2008)

A head-neck-eye system that learns fault-tolerant saccades to 3-D targets using a self-organizing neural model. - Narayan Srinivasa; Stephen Grossberg (Neural Networks, 2008)

A Bio-inspired Model for Executive Control. - Narayan Srinivasa; Suhas E. Chelian (BICA, 2010)

A bio-inspired kinematic controller for obstacle avoidance during reaching tasks with real robots. - Narayan Srinivasa; Rajan Bhattacharyya; Rashmi Sundareswara; Craig Lee; Stephen Grossberg (Neural Networks, 2012)

Energy-Efficient Neuron, Synapse and STDP Integrated Circuits. - Jose M. Cruz-Albrecht; Michael W. Yung; Narayan Srinivasa (IEEE Trans. Biomed. Circuits Syst., 2012)

Programming Time-Multiplexed Reconfigurable Hardware Using a Scalable Neuromorphic Compiler. - Kirill Minkovich; Narayan Srinivasa; Jose M. Cruz-Albrecht; Youngkwan Cho; Aleksey Nogin (IEEE Trans. Neural Networks Learn. Syst., 2012)

Self-Organizing Spiking Neural Model for Learning Fault-Tolerant Spatio-Motor Transformations. - Narayan Srinivasa; Youngkwan Cho (IEEE Trans. Neural Networks Learn. Syst., 2012)

A spiking thalamus model for form and motion processing of images. - Suhas E. Chelian; Narayan Srinivasa (IJCNN, 2013)

A compiler for scalable placement and routing of brain-like architectures. - Narayan Srinivasa (ISPD, 2013)

Learning and prospective recall of noisy spike pattern episodes. - Karl P. Dockendorf; Narayan Srinivasa (Frontiers Comput. Neurosci., 2013)

Stable learning of functional maps in self-organizing spiking neural networks with continuous synaptic plasticity. - Narayan Srinivasa; Qin Jiang (Frontiers Comput. Neurosci., 2013)

Efficiently passing messages in distributed spiking neural network simulation. - Corey M. Thibeault; Kirill Minkovich; Michael John O'Brien; Frederick C. Harris Jr.; Narayan Srinivasa (Frontiers Comput. Neurosci., 2013)

Using a hybrid neuron in physiologically inspired models of the basal ganglia. - Corey M. Thibeault; Narayan Srinivasa (Frontiers Comput. Neurosci., 2013)

A Spiking Neural Model for Stable Reinforcement of Synapses Based on Multiple Distal Rewards. - Michael John O'Brien; Narayan Srinivasa (Neural Comput., 2013)

A novel analytical characterization for short-term plasticity parameters in spiking neural networks. - Michael John O'Brien; Corey M. Thibeault; Narayan Srinivasa (Frontiers Comput. Neurosci., 2014)

Unsupervised discrimination of patterns in spiking neural networks with excitatory and inhibitory synaptic plasticity. - Narayan Srinivasa; Youngkwan Cho (Frontiers Comput. Neurosci., 2014)

Analyzing large-scale spiking neural data with HRLAnalysis™. - Corey M. Thibeault; Michael John O'Brien; Narayan Srinivasa (Frontiers Neuroinformatics, 2014)

Using Games to Embody Spiking Neural Networks for Neuromorphic Hardware. - Corey M. Thibeault; Frederick C. Harris Jr.; Narayan Srinivasa (Int. J. Comput. Their Appl., 2014)

HRLSim: A High Performance Spiking Neural Network Simulator for GPGPU Clusters. - Kirill Minkovich; Corey M. Thibeault; Michael John O'Brien; Aleksey Nogin; Youngkwan Cho; Narayan Srinivasa (IEEE Trans. Neural Networks Learn. Syst., 2014)

A Robust and Scalable Neuromorphic Communication System by Combining Synaptic Time Multiplexing and MIMO-OFDM. - Narayan Srinivasa; Deying Zhang; Beayna Grigorian (IEEE Trans. Neural Networks Learn. Syst., 2014)

Synaptic Plasticity Enables Adaptive Self-Tuning Critical Networks. - Nigel Stepp; Dietmar Plenz; Narayan Srinivasa (PLoS Comput. Biol., 2015)

Implications of a spontaneously active ground state for computing with brain-inspired circuits. - Narayan Srinivasa (ISCAS, 2017)

Learning to Recognize Actions from Limited Training Examples Using a Recurrent Spiking Neural Model. - Priyadarshini Panda; Narayan Srinivasa (CoRR, 2017)

Loihi: A Neuromorphic Manycore Processor with On-Chip Learning. - Mike Davies 002; Narayan Srinivasa; Tsung-Han Lin; Gautham N. Chinya; Yongqiang Cao; Sri Harsha Choday; Georgios D. Dimou; Prasad Joshi; Nabil Imam; Shweta Jain 005; Yuyun Liao; Chit-Kwan Lin; et al. (IEEE Micro, 2018)

Low-Power Neuromorphic Hardware for Signal Processing Applications. - Bipin Rajendran; Abu Sebastian; Michael Schmuker; Narayan Srinivasa; Evangelos Eleftheriou (CoRR, 2019)

Hypercolumn Sparsification for Low-Power Convolutional Neural Networks. - Praveen K. Pilly; Nigel Stepp; Yannis Liapis; David W. Payton; Narayan Srinivasa (ACM J. Emerg. Technol. Comput. Syst., 2019)

Low-Power Neuromorphic Hardware for Signal Processing Applications: A review of architectural and system-level design approaches. - Bipin Rajendran; Abu Sebastian; Michael Schmuker; Narayan Srinivasa; Evangelos Eleftheriou (IEEE Signal Process. Mag., 2019)

Comprehensive Integration of Hyperdimensional Computing with Deep Learning towards Neuro-Symbolic AI. - Hyunsei Lee; Jiseung Kim 005; Hanning Chen; Ariela Zeira; Narayan Srinivasa; Mohsen Imani; Yeseong Kim (DAC, 2023)

Invited Paper: Hyperdimensional Computing for Resilient Edge Learning. - Hamza Errahmouni Barkam; SungHeon Evan Jeong; Sanggeon Yun; Calvin Yeung 002; Zhuowen Zou; Xun Jiao; Narayan Srinivasa; Mohsen Imani (ICCAD, 2023)

HDReason: Algorithm-Hardware Codesign for Hyperdimensional Knowledge Graph Reasoning. - Hanning Chen; Yang Ni 001; Ali Zakeri; Zhuowen Zou; Sanggeon Yun; Fei Wen; Behnam Khaleghi; Narayan Srinivasa; Hugo Latapie; Mohsen Imani (CoRR, 2024)

Always-Sparse Training by Growing Connections with Guided Stochastic Exploration. - Mike Heddes; Narayan Srinivasa; Tony Givargis; Alex Nicolau (IJCNN, 2025)

Hyperdimensional Representation for Adaptive Information Association and Memorization. - Zhuowen Zou; Prathyush Poduval; Narayan Srinivasa; Mohsen Imani (WACV, 2025)

Enabling Efficient and Interpretable Cybersecurity Reasoning Through Hyperdimensional Computing. - Ali Zakeri; Hanning Chen; Narayan Srinivasa; Hugo Latapie; Mohsen Imani (IEEE Trans. Artif. Intell., 2025)