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ORCIDRajesh P. N. Rao
Raj P. N. Rao
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- affiliation: University of Washington, Seattle, Washington, USA
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2020 – today
- 2024
[j44]Rajesh P. N. Rao, Dimitrios C. Gklezakos, Vishwas Sathish:
Active Predictive Coding: A Unifying Neural Model for Active Perception, Compositional Learning, and Hierarchical Planning. Neural Comput. 36(1): 1-32 (2024)- [j43]Linxing Preston Jiang
, Rajesh P. N. Rao:
Dynamic predictive coding: A model of hierarchical sequence learning and prediction in the neocortex. PLoS Comput. Biol. 20(2) (2024) - 2023
- [j42]Satpreet H. Singh, Floris van Breugel, Rajesh P. N. Rao, Bingni W. Brunton:
Emergent behaviour and neural dynamics in artificial agents tracking odour plumes. Nat. Mac. Intell. 5(1): 58-70 (2023) - [c68]Linxing Preston Jiang, Rajesh P. N. Rao:
Dynamic Predictive Coding Explains Both Prediction and Postdiction in Visual Motion Perception. CogSci 2023 - [c67]Rajesh P. N. Rao, Dimitrios C. Gklezakos, Vishwas Sathish:
Active Predictive Coding: A Unified Neural Framework for Learning Hierarchical World Models for Perception and Planning. CogSci 2023 - [c66]Shirui Chen, Linxing Jiang, Rajesh P. N. Rao, Eric Shea-Brown:
Expressive probabilistic sampling in recurrent neural networks. NeurIPS 2023 - [i23]Tommaso Salvatori, Ankur Arjun Mali, Christopher L. Buckley, Thomas Lukasiewicz, Rajesh P. N. Rao, Karl J. Friston, Alexander Ororbia:
Brain-Inspired Computational Intelligence via Predictive Coding. CoRR abs/2308.07870 (2023) - [i22]Shirui Chen, Linxing Preston Jiang, Rajesh P. N. Rao, Eric Shea-Brown:
Expressive probabilistic sampling in recurrent neural networks. CoRR abs/2308.11809 (2023) - [i21]Nigini Oliveira, Jasmine Li, Koosha Khalvati, Rodolfo Cortes Barragan, Katharina Reinecke, Andrew N. Meltzoff, Rajesh P. N. Rao:
Culturally-Attuned Moral Machines: Implicit Learning of Human Value Systems by AI through Inverse Reinforcement Learning. CoRR abs/2312.17479 (2023) - 2022
- [c65]Courtnie Paschall, Rajesh P. N. Rao, Jason S. Hauptman, Jeffrey G. Ojemann, Jeffrey Herron:
An Immersive Virtual Reality Platform Integrating Human ECOG & sEEG: Implementation & Noise Analysis. EMBC 2022: 3105-3110 - [c64]Cailin Winston, Caleb Winston, Chloe N. Winston, Claris Winston, Cleah Winston, Rajesh P. N. Rao, René Just:
Repairing Brain-Computer Interfaces with Fault-Based Data Acquisition. ICSE 2022: 1869-1880 - [c63]Courtnie Jean Paschall, Jason S. Hauptman, Rajesh P. N. Rao, Jeffrey G. Ojemann, Jeffrey Herron:
Touching the Void: Intracranial Stimulation for NeuroHaptic Feedback in Virtual Reality. SMC 2022: 317-324 - [c62]Samantha Sun, Lila H. Levinson, Courtnie Jean Paschall, Jeffrey Herron, Kurt E. Weaver, Jason S. Hauptman, Andrew Ko, Jeffrey G. Ojemann, Rajesh P. N. Rao:
Human intracortical responses to varying electrical stimulation conditions are separable in low-dimensional subspaces. SMC 2022: 2663-2668 - [i20]Dimitrios C. Gklezakos, Rajesh P. N. Rao:
Active Predictive Coding Networks: A Neural Solution to the Problem of Learning Reference Frames and Part-Whole Hierarchies. CoRR abs/2201.08813 (2022) - [i19]Cailin Winston, Caleb Winston, Chloe N. Winston, Claris Winston, Cleah Winston, Rajesh P. N. Rao, René Just:
Repairing Brain-Computer Interfaces with Fault-Based Data Acquisition. CoRR abs/2203.10677 (2022) - [i18]Ares Fisher, Rajesh P. N. Rao:
Recursive Neural Programs: Variational Learning of Image Grammars and Part-Whole Hierarchies. CoRR abs/2206.08462 (2022) - [i17]Dimitrios C. Gklezakos, Rishi Jha, Rajesh P. N. Rao:
Hyper-Universal Policy Approximation: Learning to Generate Actions from a Single Image using Hypernets. CoRR abs/2207.03593 (2022) - [i16]Matthew J. Bryan, Linxing Preston Jiang, Rajesh P. N. Rao:
Neural Co-Processors for Restoring Brain Function: Results from a Cortical Model of Grasping. CoRR abs/2210.11478 (2022) - [i15]Rajesh P. N. Rao, Dimitrios C. Gklezakos, Vishwas Sathish:
Active Predictive Coding: A Unified Neural Framework for Learning Hierarchical World Models for Perception and Planning. CoRR abs/2210.13461 (2022) - 2021
- [c61]Maurice Montag, Courtnie Paschall, Jeffrey G. Ojemann, Rajesh P. N. Rao, Jeffrey Herron:
A Platform for Virtual Reality Task Design with Intracranial Electrodes. EMBC 2021: 6659-6662 - [i14]Satpreet Harcharan Singh, Floris van Breugel, Rajesh P. N. Rao, Bingni Wen Brunton:
Emergent behavior and neural dynamics in artificial agents tracking turbulent plumes. CoRR abs/2109.12434 (2021) - 2020
- [c60]Samantha Sun, Linxing Preston Jiang, Steven M. Peterson, Jeffrey Herron, Kurt E. Weaver, Andrew L. Ko, Jeffrey G. Ojemann, Rajesh P. N. Rao:
Unsupervised Sleep and Wake State Identification in Long-Term Electrocorticography Recordings. EMBC 2020: 629-632 - [c59]Satpreet H. Singh, Floris van Breugel, Rajesh P. N. Rao, Bingni W. Brunton:
Understanding biological plume tracking behavior using deep reinforcement-learning. ALIFE 2020: 750-752 - [i13]Satpreet H. Singh, Steven M. Peterson, Rajesh P. N. Rao, Bingni W. Brunton:
Towards naturalistic human neuroscience and neuroengineering: behavior mining in long-term video and neural recordings. CoRR abs/2001.08349 (2020) - [i12]Rajesh P. N. Rao:
Brain Co-Processors: Using AI to Restore and Augment Brain Function. CoRR abs/2012.03378 (2020)
2010 – 2019
- 2019
- [j41]Prashant Rangarajan, Rajesh P. N. Rao:
Estimation of Vector Autoregressive Parameters and Granger Causality From Noisy Multichannel Data. IEEE Trans. Biomed. Eng. 66(8): 2231-2240 (2019) - 2018
- [c58]Nancy Xin Ru Wang, Ali Farhadi, Rajesh P. N. Rao, Bingni W. Brunton:
AJILE Movement Prediction: Multimodal Deep Learning for Natural Human Neural Recordings and Video. AAAI 2018: 2524-2531 - [c57]Kaiyu Zheng, Andrzej Pronobis, Rajesh P. N. Rao:
Learning Graph-Structured Sum-Product Networks for Probabilistic Semantic Maps. AAAI 2018: 4547-4555 - [c56]Katie Ly, Jing Wu, Lila Levinson, Benjamin R. Shuman, Katherine M. Steele, Jeffrey G. Ojemann, Rajesh P. N. Rao:
Electrocorticographic Dynamics Predict Sustained Grasping and Upper-Limb Kinetic Output. SMC 2018: 110-114 - [i11]Linxing Jiang, Andrea Stocco, Darby M. Losey, Justin A. Abernethy, Chantel S. Prat, Rajesh P. N. Rao:
BrainNet: A Multi-Person Brain-to-Brain Interface for Direct Collaboration Between Brains. CoRR abs/1809.08632 (2018) - [i10]Rajesh P. N. Rao:
Towards Neural Co-Processors: Combining Neural Decoding and Encoding in Brain-Computer Interfaces. CoRR abs/1811.11876 (2018) - [i9]Rajesh P. N. Rao:
The Indus Script and Economics. A Role for Indus Seals and Tablets in Rationing and Administration of Labor. CoRR abs/1812.00049 (2018) - 2017
- [j40]Jimmy Baraglia, Maya Cakmak, Yukie Nagai, Rajesh P. N. Rao, Minoru Asada:
Efficient human-robot collaboration: When should a robot take initiative? Int. J. Robotics Res. 36(5-7): 563-579 (2017) - [c55]Andrzej Pronobis, Rajesh P. N. Rao:
Learning deep generative spatial models for mobile robots. IROS 2017: 755-762 - [c54]David J. Caldwell, Jing Wu, Kaitlyn Casimo, Jeffrey G. Ojemann, Rajesh P. N. Rao:
Interactive web application for exploring matrices of neural connectivity. NER 2017: 42-45 - [c53]Jing Wu, Kaitlyn Casimo, David J. Caldwell, Rajesh P. N. Rao, Jeffrey G. Ojemann:
Electrocorticographic dynamics predict visually guided motor imagery of grasp shaping. NER 2017: 199-202 - [i8]Jing Wu, Kaitlyn Casimo, David J. Caldwell, Rajesh P. N. Rao, Jeffrey G. Ojemann:
Electrocorticographic Dynamics Predict Visually Guided Motor Imagery of Grasp Shaping. CoRR abs/1702.06251 (2017) - [i7]Nancy Xin Ru Wang, Ali Farhadi, Rajesh P. N. Rao, Bingni W. Brunton:
AJILE Movement Prediction: Multimodal Deep Learning for Natural Human Neural Recordings and Video. CoRR abs/1709.05939 (2017) - [i6]Kaiyu Zheng, Andrzej Pronobis, Rajesh P. N. Rao:
Learning Semantic Maps with Topological Spatial Relations Using Graph-Structured Sum-Product Networks. CoRR abs/1709.08274 (2017) - [i5]Dimitrios C. Gklezakos, Rajesh P. N. Rao:
Transformational Sparse Coding. CoRR abs/1712.03257 (2017) - 2016
- [j39]Darby M. Losey, Andrea Stocco, Justin A. Abernethy, Rajesh P. N. Rao:
Navigating a 2D Virtual World Using Direct Brain Stimulation. Frontiers Robotics AI 3: 72 (2016) - [j38]Yanping Huang, Rajesh P. N. Rao:
Bayesian Inference and Online Learning in Poisson Neuronal Networks. Neural Comput. 28(8): 1503-1526 (2016) - [j37]Kai J. Miller, Gerwin Schalk, Dora Hermes, Jeffrey G. Ojemann, Rajesh P. N. Rao:
Spontaneous Decoding of the Timing and Content of Human Object Perception from Cortical Surface Recordings Reveals Complementary Information in the Event-Related Potential and Broadband Spectral Change. PLoS Comput. Biol. 12(1) (2016) - [j36]Jeremiah D. Wander, Devapratim Sarma, Lise A. Johnson, Eberhard E. Fetz, Rajesh P. N. Rao, Jeffrey G. Ojemann, Felix Darvas:
Cortico-Cortical Interactions during Acquisition and Use of a Neuroprosthetic Skill. PLoS Comput. Biol. 12(8) (2016) - [j35]Chet T. Moritz, Patrick Ruther, Sara Goering, Alfred Stett, Tonio Ball, Wolfram Burgard, Eric H. Chudler, Rajesh P. N. Rao:
New Perspectives on Neuroengineering and Neurotechnologies: NSF-DFG Workshop Report. IEEE Trans. Biomed. Eng. 63(7): 1354-1367 (2016) - [j34]Jeneva A. Cronin, Jing Wu, Kelly L. Collins, Devapratim Sarma, Rajesh P. N. Rao, Jeffrey G. Ojemann, Jared D. Olson:
Task-Specific Somatosensory Feedback via Cortical Stimulation in Humans. IEEE Trans. Haptics 9(4): 515-522 (2016) - [c52]Jing Wu, Benjamin R. Shuman, Bingni W. Brunton, Katherine M. Steele, Jared D. Olson, Rajesh P. N. Rao, Jeffrey G. Ojemann:
Multistep model for predicting upper-limb 3D isometric force application from pre-movement electrocorticographic features. EMBC 2016: 1564-1567 - [c51]Jimmy Baraglia, Maya Cakmak, Yukie Nagai, Rajesh P. N. Rao, Minoru Asada:
Initiative in Robot Assistance during Collaborative Task Execution. HRI 2016: 67-74 - [c50]Michael Jae-Yoon Chung, Andrzej Pronobis, Maya Cakmak, Dieter Fox, Rajesh P. N. Rao:
Autonomous question answering with mobile robots in human-populated environments. IROS 2016: 823-830 - [i4]Jing Wu, Benjamin R. Shuman, Bingni W. Brunton, Katherine M. Steele, Jared D. Olson, Rajesh P. N. Rao, Jeffrey G. Ojemann:
Multistep Model for Predicting Upper-Limb 3D Isometric Force Application from Pre-Movement Electrocorticographic Features. CoRR abs/1605.05291 (2016) - [i3]Andrzej Pronobis, Rajesh P. N. Rao:
Learning Deep Generative Spatial Models for Mobile Robots. CoRR abs/1610.02627 (2016) - 2015
- [c49]Michael Jae-Yoon Chung, Andrzej Pronobis, Maya Cakmak, Dieter Fox, Rajesh P. N. Rao:
Exploring the Potential of Information Gathering Robots. HRI (Extended Abstracts) 2015: 29-30 - [c48]Maxwell Forbes, Rajesh P. N. Rao, Luke Zettlemoyer, Maya Cakmak:
Robot Programming by Demonstration with situated spatial language understanding. ICRA 2015: 2014-2020 - [c47]Michael Jae-Yoon Chung, Andrzej Pronobis, Maya Cakmak, Dieter Fox, Rajesh P. N. Rao:
Designing information gathering robots for human-populated environments. IROS 2015: 5755-5762 - [p3]Kai J. Miller, Gerwin Schalk, Dora Hermes, Jeffrey G. Ojemann, Rajesh P. N. Rao:
Near-Instantaneous Classification of Perceptual States from Cortical Surface Recordings. Brain-Computer Interface Research (4) 2015: 105-114 - 2014
- [j33]Kai J. Miller, Christopher J. Honey, Dora Hermes, Rajesh P. N. Rao, Marcel den Nijs, Jeffrey G. Ojemann:
Broadband changes in the cortical surface potential track activation of functionally diverse neuronal populations. NeuroImage 85: 711-720 (2014) - [c46]Qiao Zhang, Shyamnath Gollakota, Ben Taskar, Raj P. N. Rao:
Non-intrusive tongue machine interface. CHI 2014: 2555-2558 - [c45]Maxwell Forbes, Michael Jae-Yoon Chung, Maya Cakmak, Rajesh P. N. Rao:
Robot Programming by Demonstration with Crowdsourced Action Fixes. HCOMP 2014: 67-76 - [c44]Michael Jae-Yoon Chung, Maxwell Forbes, Maya Cakmak, Rajesh P. N. Rao:
Accelerating imitation learning through crowdsourcing. ICRA 2014: 4777-4784 - [c43]Yanping Huang, Rajesh P. N. Rao:
Neurons as Monte Carlo Samplers: Bayesian Inference and Learning in Spiking Networks. NIPS 2014: 1943-1951 - 2012
- [j32]Xu Miao, Rajesh P. N. Rao:
Fast Structured Prediction Using Large Margin Sigmoid Belief Networks. Int. J. Comput. Vis. 99(3): 302-318 (2012) - [j31]Xu Miao, Ali Rahimi, Rajesh P. N. Rao:
Complementary Kernel Density Estimation. Pattern Recognit. Lett. 33(10): 1381-1387 (2012) - [c42]Willy Cheung, Devapratim Sarma, Reinhold Scherer, Rajesh P. N. Rao:
Simultaneous brain-computer interfacing and motor control: Expanding the reach of non-invasive BCIs. EMBC 2012: 6715-6718 - [c41]Matthew J. Bryan, Griffin Nicoll, Vibinash Thomas, Mike Chung, Joshua R. Smith, Rajesh P. N. Rao:
Automatic extraction of command hierarchies for adaptive brain-robot interfacing. ICRA 2012: 3691-3697 - [c40]Yanping Huang, Abram L. Friesen, Timothy D. Hanks, Michael N. Shadlen, Rajesh P. N. Rao:
How Prior Probability Influences Decision Making: A Unifying Probabilistic Model. NIPS 2012: 1277-1285 - 2011
- [c39]Abram L. Friesen, Rajesh P. N. Rao:
Gaze Following as Goal Inference: A Bayesian Model. CogSci 2011 - [c38]Matthew J. Bryan, Joshua Green, Mike Chung, Lillian Y. Chang, Reinhold Scherer, Joshua R. Smith, Rajesh P. N. Rao:
An adaptive brain-computer interface for humanoid robot control. Humanoids 2011: 199-204 - [c37]Mike Chung, Willy Cheung, Reinhold Scherer, Rajesh P. N. Rao:
A Hierarchical Architecture for Adaptive Brain-Computer Interfacing. IJCAI 2011: 1647-1652 - [c36]Reinhold Scherer, Elisabeth C. V. Friedrich, Brendan Z. Allison, Markus Pröll, Mike Chung, Willy Cheung, Rajesh P. N. Rao, Christa Neuper:
Non-invasive Brain-Computer Interfaces: Enhanced Gaming and Robotic Control. IWANN (1) 2011: 362-369 - 2010
- [j30]Rawichote Chalodhorn, David B. Grimes, Keith Grochow, Rajesh P. N. Rao:
Learning to Walk by Imitation in Low-Dimensional Subspaces. Adv. Robotics 24(1-2): 207-232 (2010) - [j29]Rajesh P. N. Rao, Nisha Yadav, Mayank N. Vahia, Hrishikesh Joglekar, Ronojoy Adhikari, Iravatham Mahadevan:
Entropy, the Indus Script, and Language: A Reply to R. Sproat. Comput. Linguistics 36(4): 795-805 (2010) - [j28]Rajesh P. N. Rao:
Probabilistic Analysis of an Ancient Undeciphered Script. Computer 43(4): 76-80 (2010) - [j27]Rajesh P. N. Rao:
Decision Making Under Uncertainty: A Neural Model Based on Partially Observable Markov Decision Processes. Frontiers Comput. Neurosci. 4: 146 (2010) - [j26]Andrew N. Meltzoff, Rechele Brooks, Aaron P. Shon, Rajesh P. N. Rao:
"Social" robots are psychological agents for infants: A test of gaze following. Neural Networks 23(8-9): 966-972 (2010) - [j25]Rajesh P. N. Rao, Reinhold Scherer:
Brain-Computer Interfacing [In the Spotlight]. IEEE Signal Process. Mag. 27(4): 152-150 (2010) - [c35]Abram L. Friesen, Rajesh P. N. Rao:
Imitation learning with hierarchical actions. ICDL 2010: 263-268 - [c34]Pradeep Shenoy, Rajesh P. N. Rao, Angela J. Yu:
A rational decision making framework for inhibitory control. NIPS 2010: 2146-2154 - [p2]Rawichote Chalodhorn, Rajesh P. N. Rao:
Learning to Imitate Human Actions through Eigenposes. From Motor Learning to Interaction Learning in Robots 2010: 357-381 - [i2]Xu Miao, Rajesh P. N. Rao:
Large Margin Boltzmann Machines and Large Margin Sigmoid Belief Networks. CoRR abs/1003.4781 (2010)
2000 – 2009
- 2009
- [j24]Rajesh P. N. Rao, Nisha Yadav, Mayank N. Vahia, Hrishikesh Joglekar, Ronojoy Adhikari, Iravatham Mahadevan:
A Markov model of the Indus script. Proc. Natl. Acad. Sci. USA 106(33): 13685-13690 (2009) - [c33]Xu Miao, Rajesh P. N. Rao:
Large Margin Boltzmann Machines. IJCAI 2009: 1156-1162 - [c32]Rawichote Chalodhorn, Rajesh P. N. Rao:
Using eigenposes for lossless periodic human motion imitation. IROS 2009: 2502-2509 - [p1]David B. Grimes, Rajesh P. N. Rao:
Learning Actions through Imitation and Exploration: Towards Humanoid Robots That Learn from Humans. Creating Brain-Like Intelligence 2009: 103-138 - [i1]Nisha Yadav, Hrishikesh Joglekar, Rajesh P. N. Rao, Mayank N. Vahia, Iravatham Mahadevan, Ronojoy Adhikari:
Statistical analysis of the Indus script using $n$-grams. CoRR abs/0901.3017 (2009) - 2008
- [j23]Pradeep Shenoy, Kai J. Miller, Jeffrey G. Ojemann, Rajesh P. N. Rao:
Generalized Features for Electrocorticographic BCIs. IEEE Trans. Biomed. Eng. 55(1): 273-280 (2008) - [j22]Pradeep Shenoy, Kai J. Miller, Beau Crawford, Rajesh P. N. Rao:
Online Electromyographic Control of a Robotic Prosthesis. IEEE Trans. Biomed. Eng. 55(3): 1128-1135 (2008) - [j21]Kai J. Miller, Pradeep Shenoy, Marcel den Nijs, Larry B. Sorensen, Rajesh P. N. Rao, Jeffrey G. Ojemann:
Beyond the Gamma Band: The Role of High-Frequency Features in Movement Classification. IEEE Trans. Biomed. Eng. 55(5): 1634-1637 (2008) - [c31]David B. Grimes, Desney S. Tan, Scott E. Hudson, Pradeep Shenoy, Rajesh P. N. Rao:
Feasibility and pragmatics of classifying working memory load with an electroencephalograph. CHI 2008: 835-844 - [c30]David B. Grimes, Rajesh P. N. Rao:
Learning nonparametric policies by imitation. IROS 2008: 2022-2028 - 2007
- [j20]Aaron P. Shon, Joshua J. Storz, Andrew N. Meltzoff, Rajesh P. N. Rao:
A Cognitive Model of Imitative Development in Humans and Machines. Int. J. Humanoid Robotics 4(2): 387-406 (2007) - [j19]Xu Miao, Rajesh P. N. Rao:
Learning the Lie Groups of Visual Invariance. Neural Comput. 19(10): 2665-2693 (2007) - [j18]Kai J. Miller, Marcel den Nijs, Pradeep Shenoy, John W. Miller, Rajesh P. N. Rao, Jeffrey G. Ojemann:
Real-time functional brain mapping using electrocorticography. NeuroImage 37(2): 504-507 (2007) - [c29]Aaron P. Shon, Deepak Verma, Rajesh P. N. Rao:
Active Imitation Learning. AAAI 2007: 756-762 - [c28]Deepak Verma, Rajesh P. N. Rao:
Imitation Learning Using Graphical Models. ECML 2007: 757-764 - [c27]Aaron P. Shon, Joshua J. Storz, Rajesh P. N. Rao:
Towards a Real-Time Bayesian Imitation System for a Humanoid Robot. ICRA 2007: 2847-2852 - [c26]Rawichote Chalodhorn, David B. Grimes, Keith Grochow, Rajesh P. N. Rao:
Learning to Walk through Imitation. IJCAI 2007: 2084-2090 - [c25]Jeffrey B. Cole, David B. Grimes, Rajesh P. N. Rao:
Learning full-body motions from monocular vision: dynamic imitation in a humanoid robot. IROS 2007: 240-246 - 2006
- [j17]Matthew W. Hoffman, David B. Grimes, Aaron P. Shon, Rajesh P. N. Rao:
A probabilistic model of gaze imitation and shared attention. Neural Networks 19(3): 299-310 (2006) - [c24]Rawichote Chalodhorn, David B. Grimes, Gabriel Y. Maganis, Rajesh P. N. Rao, Minoru Asada:
Learning Humanoid Motion Dynamics through Sensory-motor Mapping in Reduced Dimensional Spaces. ICRA 2006: 3693-3698 - [c23]Deepak Verma, Rajesh P. N. Rao:
Planning and Acting in Uncertain Environments using Probabilistic Inference. IROS 2006: 2382-2387 - [c22]David B. Grimes, Daniel R. Rashid, Rajesh P. N. Rao:
Learning Nonparametric Models for Probabilistic Imitation. NIPS 2006: 521-528 - [c21]David B. Grimes, Rawichote Chalodhorn, Rajesh P. N. Rao:
Dynamic Imitation in a Humanoid Robot through Nonparametric Probabilistic Inference. Robotics: Science and Systems 2006 - 2005
- [j16]Aaron P. Shon, Rajesh P. N. Rao:
Implementing belief propagation in neural circuits. Neurocomputing 65-66: 393-399 (2005) - [j15]Chris L. Baker, Aaron P. Shon, Rajesh P. N. Rao:
Learning temporal clusters with synaptic facilitation and lateral inhibition. Neurocomputing 65-66: 877-884 (2005) - [j14]David B. Grimes, Rajesh P. N. Rao:
Bilinear Sparse Coding for Invariant Vision. Neural Comput. 17(1): 47-73 (2005) - [c20]Beau Crawford, Kai J. Miller, Pradeep Shenoy, Rajesh P. N. Rao:
Real-Time Classification of Electromyographic Signals for Robotic Control. AAAI 2005: 523-528 - [c19]Aaron P. Shon, Keith Grochow, Rajesh P. N. Rao:
Robotic imitation from human motion capture using Gaussian processes. Humanoids 2005: 129-134 - [c18]Rawichote Chalodhorn, David B. Grimes, Gabriel Y. Maganis, Rajesh P. N. Rao:
Learning dynamic humanoid motion using predictive control in low dimensional subspaces. Humanoids 2005: 214-219 - [c17]Aaron P. Shon, David B. Grimes, Chris L. Baker, Matthew W. Hoffman, Shengli Zhou, Rajesh P. N. Rao:
Probabilistic Gaze Imitation and Saliency Learning in a Robotic Head. ICRA 2005: 2865-2870 - [c16]Aaron P. Shon, Keith Grochow, Aaron Hertzmann, Rajesh P. N. Rao:
Learning Shared Latent Structure for Image Synthesis and Robotic Imitation. NIPS 2005: 1233-1240 - [c15]Deepak Verma, Rajesh P. N. Rao:
Goal-Based Imitation as Probabilistic Inference over Graphical Models. NIPS 2005: 1393-1400 - 2004
- [j13]Rajesh P. N. Rao:
Bayesian Computation in Recurrent Neural Circuits. Neural Comput. 16(1): 1-38 (2004) - [c14]Rajesh P. N. Rao:
Hierarchical Bayesian Inference in Networks of Spiking Neurons. NIPS 2004: 1113-1120 - [c13]Pradeep Shenoy, Rajesh P. N. Rao:
Dynamic Bayesian Networks for Brain-Computer Interfaces. NIPS 2004: 1265-1272 - 2003
- [j12]Aaron P. Shon, Rajesh P. N. Rao:
Learning temporal patterns by redistribution of synaptic efficacy. Neurocomputing 52-54: 13-18 (2003) - [c12]David B. Grimes, Aaron P. Shon, Rajesh P. N. Rao:
Probabilistic Bilinear Models for Appearance-Based Vision. ICCV 2003: 1478-1485 - 2002
- [c11]David B. Grimes, Rajesh P. N. Rao:
A Bilinear Model for Sparse Coding. NIPS 2002: 1287-1294 - 2001
- [j11]Rajesh P. N. Rao, David M. Eagleman, Terrence J. Sejnowski:
Optimal Smoothing in Visual Motion Perception. Neural Comput. 13(6): 1243-1253 (2001) - [j10]Rajesh P. N. Rao, Terrence J. Sejnowski:
Spike-Timing-Dependent Hebbian Plasticity as Temporal Difference Learning. Neural Comput. 13(10): 2221-2237 (2001) - 2000
- [j9]Dana H. Ballard, Rajesh P. N. Rao, Zuohua Zhang:
A single-spike model of predictive coding. Neurocomputing 32-33: 17-23 (2000) - [j8]Rajesh P. N. Rao, Jörg Rothe, Osamu Watanabe:
Corrigendum to "Upward separation for FewP and related classes". Inf. Process. Lett. 74(1-2): 89 (2000)
1990 – 1999
- 1999
- [c10]Rajesh P. N. Rao, Terrence J. Sejnowski:
Predictive Sequence Learning in Recurrent Neocortical Circuits. NIPS 1999: 164-170 - 1998
- [j7]Rajesh P. N. Rao, Olac Fuentes:
Hierarchical Learning of Navigational Behaviors in an Autonomous Robot using a Predictive Sparse Distributed Memory. Auton. Robots 5(3-4): 297-316 (1998) - [j6]Rajesh P. N. Rao, Olac Fuentes:
Hierarchical Learning of Navigational Behaviors in an Autonomous Robot using a Predictive Sparse Distributed Memory. Mach. Learn. 31(1-3): 87-113 (1998) - [c9]Rajesh P. N. Rao, Daniel L. Ruderman:
Learning Lie Groups for Invariant Visual Perception. NIPS 1998: 810-816 - 1997
- [j5]Rajesh P. N. Rao, Dana H. Ballard:
Dynamic Model of Visual Recognition Predicts Neural Response Properties in the Visual Cortex. Neural Comput. 9(4): 721-763 (1997) - [c8]Rajesh P. N. Rao:
Dynamic Appearance-Based Recognition. CVPR 1997: 540-546 - [c7]Rajesh P. N. Rao:
Correlates of Attention in a Model of Dynamic Visual Recognition. NIPS 1997: 80-86 - 1995
- [j4]Rajesh P. N. Rao, Dana H. Ballard:
An Active Vision Architecture Based on Iconic Representations. Artif. Intell. 78(1-2): 461-505 (1995) - [j3]Rajesh P. N. Rao:
A Note on P-Selective Sets and Closeness. Inf. Process. Lett. 54(3): 179-185 (1995) - [c6]Dana H. Ballard, Rajesh P. N. Rao:
Towards a Functional Theory of Vision Based on Visual Routines. DAGM-Symposium 1995: 646-667 - [c5]Rajesh P. N. Rao, Dana H. Ballard:
Object Indexing Using an Iconic Sparse Distributed Memory. ICCV 1995: 24- - [c4]Rajesh P. N. Rao, Dana H. Ballard:
Natural Basis Functions and Topographic Memory for Face Recognition. IJCAI 1995: 10-19 - [c3]Rajesh P. N. Rao, Gregory J. Zelinsky, Mary M. Hayhoe, Dana H. Ballard:
Modeling Saccadic Targeting in Visual Search. NIPS 1995: 830-836 - 1994
- [j2]Rajesh P. N. Rao, Jörg Rothe, Osamu Watanabe:
Upward Separation for FewP and Related Classes. Inf. Process. Lett. 52(4): 175-180 (1994) - [c2]Dana H. Ballard, Rajesh P. N. Rao:
Seeing Behind Occlusions. ECCV (1) 1994: 274-285 - [c1]Rajesh P. N. Rao, Dana H. Ballard:
Learning Saccadic Eye Movements Using Multiscale Spatial Filters. NIPS 1994: 893-900
1980 – 1989
- 1982
- [j1]R. C. Adlakha, C. G. Sahasrabuddhe, David A. Wright, W. F. Lindsey, M. L. Smith, Rajesh P. N. Rao:
Chromosome-bound mitotic factors: release by endonucleases. Nucleic Acids Res. 10(13): 4107-4117 (1982)
Coauthor Index
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