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06/22/2023
Inertial Navigation Meets Deep Learning: A Survey of Current Trends and Future Directions
Inertial sensing is used in many applications and platforms, ranging fro...
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03/20/2023
What Makes Data Suitable for a Locally Connected Neural Network? A Necessary and Sufficient Condition Based on Quantum Entanglement
The question of what makes a data distribution suitable for deep learnin...
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12/22/2022
Set-Transformer BeamsNet for AUV Velocity Forecasting in Complete DVL Outage Scenarios
Autonomous underwater vehicles (AUVs) are regularly used for deep ocean ...
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11/29/2022
On the Ability of Graph Neural Networks to Model Interactions Between Vertices
Graph neural networks (GNNs) are widely used for modeling complex intera...
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10/25/2022
Learning Low Dimensional State Spaces with Overparameterized Recurrent Neural Network
Overparameterization in deep learning typically refers to settings where...
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10/22/2022
Deep Linear Networks for Matrix Completion – An Infinite Depth Limit
The deep linear network (DLN) is a model for implicit regularization in ...
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10/20/2022
LiBeamsNet: AUV Velocity Vector Estimation in Situations of Limited DVL Beam Measurements
Autonomous underwater vehicles (AUVs) are employed for marine applicatio...
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06/27/2022
BeamsNet: A data-driven Approach Enhancing Doppler Velocity Log Measurements for Autonomous Underwater Vehicle Navigation
Autonomous underwater vehicles (AUV) perform various applications such a...
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03/07/2022
Semantic Segmentation in Art Paintings
Semantic segmentation is a difficult task even when trained in a supervi...
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02/09/2022
On the Implicit Bias of Gradient Descent for Temporal Extrapolation
Common practice when using recurrent neural networks (RNNs) is to apply ...
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01/27/2022
Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks
In the pursuit of explaining implicit regularization in deep learning, p...
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07/14/2021
Continuous vs. Discrete Optimization of Deep Neural Networks
Existing analyses of optimization in deep learning are either continuous...
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02/19/2021
Implicit Regularization in Tensor Factorization
Implicit regularization in deep learning is perceived as a tendency of g...
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05/13/2020
Implicit Regularization in Deep Learning May Not Be Explainable by Norms
Mathematically characterizing the implicit regularization induced by gra...
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05/31/2019
Implicit Regularization in Deep Matrix Factorization
Efforts to understand the generalization mystery in deep learning have l...
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10/04/2018
A Convergence Analysis of Gradient Descent for Deep Linear Neural Networks
We analyze speed of convergence to global optimum for gradient descent t...
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03/26/2018
Bridging Many-Body Quantum Physics and Deep Learning via Tensor Networks
The harnessing of modern computational abilities for many-body wave-func...
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02/19/2018
On the Optimization of Deep Networks: Implicit Acceleration by Overparameterization
Conventional wisdom in deep learning states that increasing depth improv...
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12/17/2017
"Zero-Shot" Super-Resolution using Deep Internal Learning
Deep Learning has led to a dramatic leap in Super-Resolution (SR) perfor...
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05/05/2017
Analysis and Design of Convolutional Networks via Hierarchical Tensor Decompositions
The driving force behind convolutional networks - the most successful de...
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04/05/2017
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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03/20/2017
Boosting Dilated Convolutional Networks with Mixed Tensor Decompositions
The driving force behind deep networks is their ability to compactly rep...
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10/13/2016
Tractable Generative Convolutional Arithmetic Circuits
Casting neural networks in generative frameworks is a highly sought-afte...
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05/22/2016
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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03/01/2016
Convolutional Rectifier Networks as Generalized Tensor Decompositions
Convolutional rectifier networks, i.e. convolutional neural networks wit...
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09/16/2015
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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06/09/2015
