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04/03/2023
Diffusion Bridge Mixture Transports, Schrödinger Bridge Problems and Generative Modeling
The dynamic Schrödinger bridge problem seeks a stochastic process that d...
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06/16/2022
Neural tangent kernel analysis of shallow α-Stable ReLU neural networks
There is a recent literature on large-width properties of Gaussian neura...
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08/02/2021
Deep Stable neural networks: large-width asymptotics and convergence rates
In modern deep learning, there is a recent and growing literature on the...
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06/07/2021
Learning Stochastic Optimal Policies via Gradient Descent
We systematically develop a learning-based treatment of stochastic optim...
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02/20/2021
Large-width functional asymptotics for deep Gaussian neural networks
In this paper, we consider fully connected feed-forward deep neural netw...
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02/08/2021
Learning-augmented count-min sketches via Bayesian nonparametrics
The count-min sketch (CMS) is a time and memory efficient randomized dat...
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02/07/2021
A Bayesian nonparametric approach to count-min sketch under power-law data streams
The count-min sketch (CMS) is a randomized data structure that provides ...
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02/07/2021
Infinite-channel deep stable convolutional neural networks
The interplay between infinite-width neural networks (NNs) and classes o...
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07/07/2020
Doubly infinite residual networks: a diffusion process approach
When neural network's parameters are initialized as i.i.d., neural netwo...
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03/01/2020
Stable behaviour of infinitely wide deep neural networks
We consider fully connected feed-forward deep neural networks (NNs) wher...
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10/03/2019
An empirical study of pretrained representations for few-shot classification
Recent algorithms with state-of-the-art few-shot classification results ...
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05/27/2019
