Narayan Srinivasa

56 papers A* 2A 3B 7C 1Journal 34Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Emissions transparency in AI research should be mandatory. Sustain. Comput. Informatics Syst. Malka N. Halgamuge, Narayan Srinivasa
2025	B	`conf`	Always-Sparse Training by Growing Connections with Guided Stochastic Exploration. IJCNN Mike Heddes, Narayan Srinivasa, Tony Givargis, Alex Nicolau
2025	J	`jnl`	Enabling Efficient and Interpretable Cybersecurity Reasoning Through Hyperdimensional Computing. IEEE Trans. Artif. Intell. Ali Zakeri, Hanning Chen, Narayan Srinivasa, Hugo Latapie, Mohsen Imani
2025	A	`conf`	Hyperdimensional Representation for Adaptive Information Association and Memorization. WACV Zhuowen Zou, Prathyush Poduval, Narayan Srinivasa, Mohsen Imani
2024	J	`jnl`	Always-Sparse Training by Growing Connections with Guided Stochastic Exploration. CoRR Mike Heddes, Narayan Srinivasa, Tony Givargis, Alexandru Nicolau
2024	J	`jnl`	HDReason: Algorithm-Hardware Codesign for Hyperdimensional Knowledge Graph Reasoning. CoRR Hanning Chen, Yang Ni, Ali Zakeri, Zhuowen Zou, Sanggeon Yun, Fei Wen, Behnam Khaleghi, Narayan Srinivasa, Hugo Latapie, Mohsen Imani
2023	A*	`conf`	Comprehensive Integration of Hyperdimensional Computing with Deep Learning towards Neuro-Symbolic AI. DAC Hyunsei Lee, Jiseung Kim, Hanning Chen, Ariela Zeira, Narayan Srinivasa, Mohsen Imani, Yeseong Kim
2023	A	`conf`	Invited Paper: Hyperdimensional Computing for Resilient Edge Learning. ICCAD Hamza Errahmouni Barkam, SungHeon Evan Jeong, Sanggeon Yun, Calvin Yeung, Zhuowen Zou, Xun Jiao, Narayan Srinivasa, Mohsen Imani
2019	J	`jnl`	Hypercolumn Sparsification for Low-Power Convolutional Neural Networks. ACM J. Emerg. Technol. Comput. Syst. Praveen K. Pilly, Nigel Stepp, Yannis Liapis, David W. Payton, Narayan Srinivasa
2019	J	`jnl`	Low-Power Neuromorphic Hardware for Signal Processing Applications. CoRR Bipin Rajendran, Abu Sebastian, Michael Schmuker, Narayan Srinivasa, Evangelos Eleftheriou
2019	J	`jnl`	Low-Power Neuromorphic Hardware for Signal Processing Applications: A review of architectural and system-level design approaches. IEEE Signal Process. Mag. Bipin Rajendran, Abu Sebastian, Michael Schmuker, Narayan Srinivasa, Evangelos Eleftheriou
2018	J	`jnl`	Loihi: A Neuromorphic Manycore Processor with On-Chip Learning. IEEE Micro Mike Davies, Narayan Srinivasa, Tsung-Han Lin, Gautham N. Chinya, Yongqiang Cao, Sri Harsha Choday, Georgios D. Dimou, Prasad Joshi, Nabil Imam, Shweta Jain, Yuyun Liao, Chit-Kwan Lin, Andrew Lines, Ruokun Liu, Deepak Mathaikutty, Steven McCoy, Arnab Paul, Jonathan Tse, Guruguhanathan Venkataramanan, Yi-Hsin Weng, Andreas Wild, Yoonseok Yang, Hong Wang
2017	C	`conf`	Implications of a spontaneously active ground state for computing with brain-inspired circuits. ISCAS Narayan Srinivasa
2017	J	`jnl`	Learning to Recognize Actions from Limited Training Examples Using a Recurrent Spiking Neural Model. CoRR Priyadarshini Panda, Narayan Srinivasa
2015	J	`jnl`	Synaptic Plasticity Enables Adaptive Self-Tuning Critical Networks. PLoS Comput. Biol. Nigel Stepp, Dietmar Plenz, Narayan Srinivasa
2014	J	`jnl`	A Robust and Scalable Neuromorphic Communication System by Combining Synaptic Time Multiplexing and MIMO-OFDM. IEEE Trans. Neural Networks Learn. Syst. Narayan Srinivasa, Deying Zhang, Beayna Grigorian
2014	J	`jnl`	A novel analytical characterization for short-term plasticity parameters in spiking neural networks. Frontiers Comput. Neurosci. Michael John O'Brien, Corey M. Thibeault, Narayan Srinivasa
2014	J	`jnl`	Analyzing large-scale spiking neural data with HRLAnalysis™. Frontiers Neuroinformatics Corey M. Thibeault, Michael John O'Brien, Narayan Srinivasa
2014	J	`jnl`	HRLSim: A High Performance Spiking Neural Network Simulator for GPGPU Clusters. IEEE Trans. Neural Networks Learn. Syst. Kirill Minkovich, Corey M. Thibeault, Michael John O'Brien, Aleksey Nogin, Youngkwan Cho, Narayan Srinivasa
2014	J	`jnl`	Unsupervised discrimination of patterns in spiking neural networks with excitatory and inhibitory synaptic plasticity. Frontiers Comput. Neurosci. Narayan Srinivasa, Youngkwan Cho
2014	J	`jnl`	Using Games to Embody Spiking Neural Networks for Neuromorphic Hardware. Int. J. Comput. Their Appl. Corey M. Thibeault, Frederick C. Harris Jr., Narayan Srinivasa
2013	J	`jnl`	A Spiking Neural Model for Stable Reinforcement of Synapses Based on Multiple Distal Rewards. Neural Comput. Michael John O'Brien, Narayan Srinivasa
2013	—	`conf`	A compiler for scalable placement and routing of brain-like architectures. ISPD Narayan Srinivasa
2013	B	`conf`	A spiking thalamus model for form and motion processing of images. IJCNN Suhas E. Chelian, Narayan Srinivasa
2013	J	`jnl`	Efficiently passing messages in distributed spiking neural network simulation. Frontiers Comput. Neurosci. Corey M. Thibeault, Kirill Minkovich, Michael John O'Brien, Frederick C. Harris Jr., Narayan Srinivasa
2013	J	`jnl`	Learning and prospective recall of noisy spike pattern episodes. Frontiers Comput. Neurosci. Karl P. Dockendorf, Narayan Srinivasa
2013	J	`jnl`	Stable learning of functional maps in self-organizing spiking neural networks with continuous synaptic plasticity. Frontiers Comput. Neurosci. Narayan Srinivasa, Qin Jiang
2013	J	`jnl`	Using a hybrid neuron in physiologically inspired models of the basal ganglia. Frontiers Comput. Neurosci. Corey M. Thibeault, Narayan Srinivasa
2012	J	`jnl`	A bio-inspired kinematic controller for obstacle avoidance during reaching tasks with real robots. Neural Networks Narayan Srinivasa, Rajan Bhattacharyya, Rashmi Sundareswara, Craig Lee, Stephen Grossberg
2012	J	`jnl`	Energy-Efficient Neuron, Synapse and STDP Integrated Circuits. IEEE Trans. Biomed. Circuits Syst. Jose M. Cruz-Albrecht, Michael W. Yung, Narayan Srinivasa
2012	J	`jnl`	Programming Time-Multiplexed Reconfigurable Hardware Using a Scalable Neuromorphic Compiler. IEEE Trans. Neural Networks Learn. Syst. Kirill Minkovich, Narayan Srinivasa, Jose M. Cruz-Albrecht, Youngkwan Cho, Aleksey Nogin
2012	J	`jnl`	Self-Organizing Spiking Neural Model for Learning Fault-Tolerant Spatio-Motor Transformations. IEEE Trans. Neural Networks Learn. Syst. Narayan Srinivasa, Youngkwan Cho
2010	—	`conf`	A Bio-inspired Model for Executive Control. BICA Narayan Srinivasa, Suhas E. Chelian
2008	J	`jnl`	A head-neck-eye system that learns fault-tolerant saccades to 3-D targets using a self-organizing neural model. Neural Networks Narayan Srinivasa, Stephen Grossberg
2008	—	`conf`	Bio-Inspired Planning and Reaching in Complex Environments. AAAI Fall Symposium: Biologically Inspired Cognitive Architectures Rajan Bhattacharyya, Narayan Srinivasa, Stephen Grossberg
2008	—	`conf`	High-Impact Event Prediction by Temporal Data Mining through Genetic Algorithms. ICNC (1) Narayan Srinivasa, Qin Jiang, Leandro G. Barajas
2008	—	`conf`	Learning Invariant Sensory-Motor Transforms for Fault-Tolerant Control of Redundant Robots. AAAI Fall Symposium: Biologically Inspired Cognitive Architectures Narayan Srinivasa, Stephen Grossberg
2007	B	`conf`	A Self-Organizing Neural Model for Fault-Tolerant Control of Redundant Robots. IJCNN Narayan Srinivasa, Stephen Grossberg
2005	—	`conf`	Modeling of pedestrian motion for recognition. Electronic Imaging: Image and Video Communications and Processing Payam Saisan, Swarup Medasani, Narayan Srinivasa, Yuri Owechko
2004	B	`conf`	Active fuzzy clustering for collaborative filtering. FUZZ-IEEE Narayan Srinivasa, Swarup Medasani
2004	B	`conf`	Active learning system for object fingerprinting. IJCNN Swarup Medasani, Narayan Srinivasa, Yuri Owechko
2004	—	`conf`	Classifier Swarms for Human Detection in Infrared Imagery. CVPR Workshops Yuri Owechko, Swarup Medasani, Narayan Srinivasa
2003	B	`conf`	Fuzzy edge-symmetry features for improved intruder detection. FUZZ-IEEE Narayan Srinivasa, Swarup Medasani, Yuri Owechko, Deepak Khosla
2001	B	`conf`	An On-line Method for Self Organized Learningn and Extraction of Fuzzy From High Dimensional Data. FUZZ-IEEE Swarup Medasani, Narayan Srinivasa, Yuri Owechko
1999	J	`jnl`	A topological and temporal correlator network for spatiotemporal pattern learning, recognition, and recall. IEEE Trans. Neural Networks Narayan Srinivasa, Narendra Ahuja
1998	—	`conf`	A Learning Approach to Fixating on 3D Targets with Active Cameras. ACCV (1) Narayan Srinivasa, Narendra Ahuja
1998	J	`jnl`	A framework for active vision-based robot control using neural networks. Robotica Rajeev Sharma, Narayan Srinivasa
1998	J	`jnl`	Efficient Learning of VAM-Based Representation of 3D Targets and its Active Vision Applications. Neural Networks Narayan Srinivasa, Rajeev Sharma
1998	—	`conf`	Learning Multiscale Image Models of 2D Object Classes. ACCV (2) Benoit Perrin, Narendra Ahuja, Narayan Srinivasa
1997	J	`jnl`	Grasping and in-hand manipulation: experiments with a reconfigurable gripper. Adv. Robotics Attawith Sudsang, Jean Ponce, Narayan Srinivasa
1997	J	`jnl`	Learning and generalization of noisy mappings using a modified PROBART neural network. IEEE Trans. Signal Process. Narayan Srinivasa
1997	A	`conf`	On planning immobilizing grasps for a reconfigurable gripper. IROS Attawith Sudsang, Narayan Srinivasa, Jean Ponce
1997	J	`jnl`	SOIM: a self-organizing invertible map with applications in active vision. IEEE Trans. Neural Networks Narayan Srinivasa, Rajeev Sharma
1996	A*	`conf`	A framework for robot control with active vision using a neural network based spatial representation. ICRA Rajeev Sharma, Narayan Srinivasa
1993	J	`jnl`	An invariant pattern recognition machine using a modified ART architecture. IEEE Trans. Syst. Man Cybern. Narayan Srinivasa, Musa K. Jouaneh
1992	J	`jnl`	A neural network model for invariant pattern recognition. IEEE Trans. Signal Process. Narayan Srinivasa, Musa K. Jouaneh