10 citations · 11 across the 5 of their papers we have counts for
8 papers
Exact Topological Compliance: Generating Persistence-Equivalent Graphs
Mattie Ji, Indradyumna Roy, Vikas Garg
Persistent homology summarizes the topological evolution of a graph as persistence diagrams (PDs). Generating graphs whose topology matches a target descriptor is increasingly impo…
The Logical Expressiveness of Topological Neural Networks
Amirreza Akbari, Amauri H. Souza, Vikas Garg
Graph neural networks (GNNs) are the standard for learning on graphs, yet they have limited expressive power, often expressed in terms of the Weisfeiler-Leman (WL) hierarchy or wit…
On topological descriptors for graph products
Mattie Ji, Amauri H. Souza, Vikas Garg
Topological descriptors have been increasingly utilized for capturing multiscale structural information in relational data. In this work, we consider various filtrations on the (bo…
Graph Persistence goes Spectral
Mattie Ji, Amauri H. Souza, Vikas Garg
Including intricate topological information (e.g., cycles) provably enhances the expressivity of message-passing graph neural networks (GNNs) beyond the Weisfeiler-Leman (WL) hiera…
Employing Federated Learning for Training Autonomous HVAC Systems
Fredrik Hagström, Vikas Garg, Fabricio Oliveira
Buildings account for 40% of global energy consumption. A considerable portion of building energy consumption stems from heating, ventilation, and air conditioning (HVAC), and thus…
Algebraic Positional Encodings
Konstantinos Kogkalidis, Jean-Philippe Bernardy, Vikas Garg
We introduce a novel positional encoding strategy for Transformer-style models, addressing the shortcomings of existing, often ad hoc, approaches. Our framework provides a flexible…
Going beyond persistent homology using persistent homology
Johanna Immonen, Amauri H. Souza, Vikas Garg
Representational limits of message-passing graph neural networks (MP-GNNs), e.g., in terms of the Weisfeiler-Leman (WL) test for isomorphism, are well understood. Augmenting these…
Compositional Sculpting of Iterative Generative Processes
Timur Garipov, Sebastiaan De Peuter, Ge Yang +3
High training costs of generative models and the need to fine-tune them for specific tasks have created a strong interest in model reuse and composition. A key challenge in composi…