Dileep George

Q: What Schools Are Affiliated With Dileep George

Dileep George is affiliated with the following schools: Stanford University, IIT Bombay

Dileep George's AcademicInfluence.com Rankings

Dileep George

Computer Science

#1118

World Rank

#1158

Historical Rank

#589

USA Rank

Artificial Intelligence

#73

World Rank

#76

Historical Rank

#34

USA Rank

Algorithms

#174

World Rank

#177

Historical Rank

#29

USA Rank

Machine Learning

#802

World Rank

#813

Historical Rank

#85

USA Rank

computer-science Degrees

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Computer Science

Dileep George's Degrees

PhD Electrical Engineering Stanford University
Masters Electrical Engineering Stanford University

Why Is Dileep George Influential?

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According to Wikipedia, Dileep George is an artificial intelligence and neuroscience researcher. Career George received his PhD in Electrical Engineering from Stanford University in 2006 and was a visiting fellow at the Redwood Center for Theoretical Neuroscience at the University of California, Berkeley.

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Dileep George's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

Towards a Mathematical Theory of Cortical Micro-circuits (2009) (421)
A hierarchical Bayesian model of invariant pattern recognition in the visual cortex (2005) (243)
A generative vision model that trains with high data efficiency and breaks text-based CAPTCHAs (2017) (217)
Hierarchical Temporal Memory Concepts , Theory , and Terminology (2006) (207)
Schema Networks: Zero-shot Transfer with a Generative Causal Model of Intuitive Physics (2017) (202)
How the brain might work: a hierarchical and temporal model for learning and recognition (2008) (188)
Sequence memory for prediction, inference and behaviour (2009) (84)
Beyond imitation: Zero-shot task transfer on robots by learning concepts as cognitive programs (2018) (61)
Letter to the Editor: Research Priorities for Robust and Beneficial Artificial Intelligence: An Open Letter (2015) (49)
Teaching Compositionality to CNNs (2017) (46)
Invariant Pattern Recognition using Bayesian Inference on Hierarchical Sequences (2004) (29)
Robust Induction of Process Models from Time-Series Data (2003) (24)
Clone-structured graph representations enable flexible learning and vicarious evaluation of cognitive maps (2021) (23)
Behavior Is Everything: Towards Representing Concepts with Sensorimotor Contingencies (2018) (21)
Learning higher-order sequential structure with cloned HMMs (2019) (13)
Hierarchical Temporal Memory: Theory and Applications (2006) (12)
Belief Propagation and Wiring Length Optimization as Organizing Principles for Cortical Microcircuits (2005) (11)
Hierarchical compositional feature learning (2016) (10)
From CAPTCHA to Commonsense: How Brain Can Teach Us About Artificial Intelligence (2020) (9)
Generative Shape Models: Joint Text Recognition and Segmentation with Very Little Training Data (2016) (9)
Cortical Microcircuits from a Generative Vision Model (2018) (8)
Memorize-Generalize: An online algorithm for learning higher-order sequential structure with cloned Hidden Markov Models (2019) (8)
Computing with inter-spike interval codes in networks of integrate and fire neurons (2005) (6)
Query Training: Learning a Worse Model to Infer Better Marginals in Undirected Graphical Models with Hidden Variables (2020) (6)
A detailed mathematical theory of thalamic and cortical microcircuits based on inference in a generative vision model (2020) (5)
Learning a generative model for robot control using visual feedback (2020) (5)
Explaining Visual Cortex Phenomena using Recursive Cortical Network (2018) (4)
Learning cognitive maps as structured graphs for vicarious evaluation (2019) (4)
Discovering Ecosystem Models from Time-Series Data (2003) (4)
Sample-efficient L0-L2 constrained structure learning of sparse Ising models (2020) (3)
How to make computers that work like the brain (2009) (3)
What can the brain teach us about building artificial intelligence? (2017) (3)
Learning cognitive maps for vicarious evaluation (2019) (3)
Perturb-and-max-product: Sampling and learning in discrete energy-based models (2021) (2)
A Model of Fast Concept Inference with Object-Factorized Cognitive Programs (2020) (2)
PGMax: Factor Graphs for Discrete Probabilistic Graphical Models and Loopy Belief Propagation in JAX (2022) (2)
Learning attention-controllable border-ownership for objectness inference and binding (2021) (2)
DURableVS: Data-efficient Unsupervised Recalibrating Visual Servoing via online learning in a structured generative model (2022) (1)
Space is a latent sequence: Structured sequence learning as a unified theory of representation in the hippocampus (2022) (1)
Query Training: Learning and inference for directed and undirected graphical models (2020) (1)
Learning undirected models via query training (2019) (1)
Different clones for different contexts: Hippocampal cognitive maps as higher-order graphs of a cloned HMM (2019) (1)
Graphical Models with Attention for Context-Specific Independence and an Application to Perceptual Grouping (2021) (1)
Learning noisy-OR Bayesian Networks with Max-Product Belief Propagation (2023) (1)
2 Short-term Research Priorities 2 . 1 Optimizing AI ’ s Economic Impact (0)
Low Complexity Schemes for Long Term Memory Motion Compensation (2003) (0)
From proprioception to long-horizon planning in novel environments: A hierarchical RL model (2020) (0)
Mapping between neocortex hierarchy and HTM hierarchy. (2009) (0)
A HierarchicalBayesianModel of Invariant Pattern Recognition intheVisualCortex (2005) (0)
Graph schemas as abstractions for transfer learning, inference, and planning (2023) (0)
3D Neural Embedding Likelihood for Robust Probabilistic Inverse Graphics (2023) (0)
Inducing Biological Models from Temporal Gene Expression Data (2003) (0)
Fast exploration and learning of latent graphs with aliased observations (2023) (0)
PushWorld: A benchmark for manipulation planning with tools and movable obstacles (2023) (0)
Interactive learning of cognitive programs (2020) (0)
3D Neural Embedding Likelihood for Robust Sim-to-Real Transfer in Inverse Graphics (2023) (0)
A backward pass through a CNN using a generative model of its activations (2016) (0)

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Other Resources About Dileep George

What Schools Are Affiliated With Dileep George?

Dileep George is affiliated with the following schools:

Dileep George's Academic­Influence.com Rankings

Dileep George's Degrees

Why Is Dileep George Influential?

Dileep George's Published Works

Published Works

Other Resources About Dileep George

What Schools Are Affiliated With Dileep George?

Dileep George's AcademicInfluence.com Rankings