2 citations · 5 across the 7 of their papers we have counts for
7 papers
Emergence of heavy tails in homogenized stochastic gradient descent
Zhe Jiao, Martin Keller-Ressel
It has repeatedly been observed that loss minimization by stochastic gradient descent (SGD) leads to heavy-tailed distributions of neural network parameters. Here, we analyze a con…
Hyperbolic Deep Learning in Computer Vision: A Survey
Pascal Mettes, Mina Ghadimi Atigh, Martin Keller-Ressel +2
Deep representation learning is a ubiquitous part of modern computer vision. While Euclidean space has been the de facto standard manifold for learning visual representations, hype…
State space decomposition and classification of term structure shapes in the two-factor Vasicek model
Martin Keller-Ressel, Felix Sachse
Using the concept of envelopes we show how to divide the state space $\RR^2$ of the two-factor Vasicek model into regions of identical term-structure shape. We develop a formula fo…
Bartlett's Delta revisited: Variance-optimal hedging in the lognormal SABR and in the rough Bergomi model
Martin Keller-Ressel
We derive analytic expressions for the variance-optimal hedging strategy and its mean-square hedging error in the lognormal SABR and in the rough Bergomi model. In the SABR model,…
Strain-Minimizing Hyperbolic Network Embeddings with Landmarks
Martin Keller-Ressel, Stephanie Nargang
We introduce L-hydra (landmarked hyperbolic distance recovery and approximation), a method for embedding network- or distance-based data into hyperbolic space, which requires only…
Geometric Asian Option Pricing in General Affine Stochastic Volatility Models with Jumps
Friedrich Hubalek, Martin Keller-Ressel, Carlo Sgarra
In this paper we present some results on Geometric Asian option valuation for affine stochastic volatility models with jumps. We shall provide a general framework into which severa…