
Analysis and Design of Convolutional Networks via Hierarchical Tensor Decompositions
The driving force behind convolutional networks  the most successful de...
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Deep Learning and Quantum Entanglement: Fundamental Connections with Implications to Network Design
Deep convolutional networks have witnessed unprecedented success in vari...
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Boosting Dilated Convolutional Networks with Mixed Tensor Decompositions
The driving force behind deep networks is their ability to compactly rep...
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On a Formal Model of Safe and Scalable Selfdriving Cars
In recent years, car makers and tech companies have been racing towards ...
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Inductive Bias of Deep Convolutional Networks through Pooling Geometry
Our formal understanding of the inductive bias that drives the success o...
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Convolutional Rectifier Networks as Generalized Tensor Decompositions
Convolutional rectifier networks, i.e. convolutional neural networks wit...
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Deep SimNets
We present a deep layered architecture that generalizes convolutional ne...
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On the Expressive Power of Overlapping Architectures of Deep Learning
Expressive efficiency refers to the relation between two architectures A...
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Tractable Generative Convolutional Arithmetic Circuits
Casting neural networks in generative frameworks is a highly soughtafte...
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Safe, MultiAgent, Reinforcement Learning for Autonomous Driving
Autonomous driving is a multiagent setting where the host vehicle must ...
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On the Expressive Power of Deep Learning: A Tensor Analysis
It has long been conjectured that hypotheses spaces suitable for data th...
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Learning a Metric Embedding for Face Recognition using the Multibatch Method
This work is motivated by the engineering task of achieving a near state...
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Tightening Fractional Covering Upper Bounds on the Partition Function for HighOrder Region Graphs
In this paper we present a new approach for tightening upper bounds on t...
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ShareBoost: Efficient Multiclass Learning with Feature Sharing
Multiclass prediction is the problem of classifying an object into a rel...
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SumProductQuotient Networks
We present a novel tractable generative model that extends SumProduct N...
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Benefits of Depth for LongTerm Memory of Recurrent Networks
The key attribute that drives the unprecedented success of modern Recurr...
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Bridging ManyBody Quantum Physics and Deep Learning via Tensor Networks
The harnessing of modern computational abilities for manybody wavefunc...
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Vision Zero: on a Provable Method for Eliminating Roadway Accidents without Compromising Traffic Throughput
We propose an economical, viable, approach to eliminate almost all car a...
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Deep autoregressive models for the efficient variational simulation of manybody quantum systems
Artificial Neural Networks were recently shown to be an efficient repres...
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SenseBERT: Driving Some Sense into BERT
Selfsupervision techniques have allowed neural language models to advan...
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Amnon Shashua
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Computer science faculty at the Hebrew University of Jerusalem since 1996, Associate Professor of Computer Science at the Hebrew University of Jerusalem from 19992003, Professor of Computer Science at the Hebrew University of Jerusalem since 1996, Full Professor of Computer Science at the Hebrew University of Jerusalem since 2003, Head of the engineering and computer science school at the Hebrew University 20022005, Sachs chair in computer science at the Hebrew University.