Bastian Rieck

Full Professor@University of Fribourg·瑞士·OpenReview

研究方向

persistent homology · computational topology · topological data analysis · topological machine learning · geometric deep learning · topological deep learning · graph learning

Bastian Rieck

LEAP: Local ECT-Based Learnable Positional Encodings for Graphs

TOAST : Transformer Optimization using Adaptive and Simple Transformations

Less is More: Local Intrinsic Dimensions of Contextual Language Models

MAGNet: Motif-Agnostic Generation of Molecules from Scaffolds

No Metric to Rule Them All: Toward Principled Evaluations of Graph-Learning Datasets

Point Cloud Synthesis Using Inner Product Transforms

Geometry-Aware Edge Pooling for Graph Neural Networks

Diss-l-ECT: Dissecting Graph Data with Local Euler Characteristic Transforms

Diss-l-ECT: Dissecting Graph Data with local Euler Characteristic Transforms

MANTRA: The Manifold Triangulations Assemblage

Detecting and Approximating Redundant Computational Blocks in Neural Networks

Generative Topology for Shape Synthesis