1 citations · 1 across the 3 of their papers we have counts for
4 papers
Flood and Echo Net: Algorithmically Aligned GNNs that Generalize
Joël Mathys, Florian Grötschla, Kalyan Varma Nadimpalli +1
Most Graph Neural Networks follow the standard message-passing framework where, in each step, all nodes simultaneously communicate with each other. We want to challenge this paradi…
ICML 2023 Topological Deep Learning Challenge : Design and Results
Mathilde Papillon, Mustafa Hajij, Helen Jenne +53
This paper presents the computational challenge on topological deep learning that was hosted within the ICML 2023 Workshop on Topology and Geometry in Machine Learning. The competi…
Euler Characteristic Transform Based Topological Loss for Reconstructing 3D Images from Single 2D Slices
Kalyan Varma Nadimpalli, Amit Chattopadhyay, Bastian Rieck
The computer vision task of reconstructing 3D images, i.e., shapes, from their single 2D image slices is extremely challenging, more so in the regime of limited data. Deep learning…
A Robust Classification Framework for Byzantine-Resilient Stochastic Gradient Descent
Shashank Reddy Chirra, Kalyan Varma Nadimpalli, Shrisha Rao
This paper proposes a Robust Gradient Classification Framework (RGCF) for Byzantine fault tolerance in distributed stochastic gradient descent. The framework consists of a pattern…