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Antonov and Piterbarg – 22/11/22

Nov 24, 2022
33:10
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1
Introduction
00:00 • 4min
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2
The Black Box Effect in Neural Networks
04:25 • 2min
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3
Languages Are Stable Over Time
06:12 • 2min
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4
The Problem of Approximation of Functions in Finance
08:00 • 3min
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5
Generalized Stochastic Sampling in Multi-Dimensional Space
10:36 • 3min
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6
Interpolating Functions in One Dimension
13:32 • 2min
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7
How Does Deep Neural Network Work?
15:05 • 3min
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8
The Functional Tensor Train
17:39 • 2min
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9
The Tensor Train Extension
19:31 • 4min
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10
Towards the Output Voice Requires Computational Efficiency
23:46 • 2min
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11
Application to Finance
25:56 • 4min
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12
The Comparison Between Deep Neural Networks and XVA
29:59 • 3min
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A discussion around alternatives designed to overcome the pitfalls of neural networks.
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