
A Representational Model of Grid Cells Based on Matrix Lie Algebras
The grid cells in the mammalian medial entorhinal cortex exhibit strikin...
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Learning Energybased Model with Flowbased Backbone by Neural Transport MCMC
Learning energybased model (EBM) requires MCMC sampling of the learned ...
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Flow Contrastive Estimation of EnergyBased Models
This paper studies a training method to jointly estimate an energybased...
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Representation Learning: A Statistical Perspective
Learning representations of data is an important problem in statistics a...
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MotionBased Generator Model: Unsupervised Disentanglement of Appearance, Trackable and Intrackable Motions in Dynamic Patterns
Dynamic patterns are characterized by complex spatial and motion pattern...
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Convergence of Adversarial Training in Overparametrized Networks
Neural networks are vulnerable to adversarial examples, i.e. inputs that...
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A GramGaussNewton Method Learning Overparameterized Deep Neural Networks for Regression Problems
Firstorder methods such as stochastic gradient descent (SGD) are curren...
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Learning Vector Representation of Content and Matrix Representation of Change: Towards a Representational Model of V1
This paper entertains the hypothesis that the primary purpose of the cel...
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Learning Dynamic Generator Model by Alternating BackPropagation Through Time
This paper studies the dynamic generator model for spatialtemporal proc...
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Learning Gridlike Units with Vector Representation of SelfPosition and Matrix Representation of SelfMotion
This paper proposes a model for learning gridlike units for spatial awa...
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A Tale of Three Probabilistic Families: Discriminative, Descriptive and Generative Models
The pattern theory of Grenander is a mathematical framework where the pa...
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Deformable Generator Network: Unsupervised Disentanglement of Appearance and Geometry
We propose a deformable generator model to disentangle the appearance an...
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Learning Descriptor Networks for 3D Shape Synthesis and Analysis
This paper proposes a 3D shape descriptor network, which is a deep convo...
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Learning Multigrid Generative ConvNets by Minimal Contrastive Divergence
This paper proposes a minimal contrastive divergence method for learning...
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Cooperative Training of Descriptor and Generator Networks
This paper studies the cooperative training of two probabilistic models ...
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Ruiqi Gao
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