Post #126

Geometric and Relational Deep Learning Pt. 2 Apparently in this workshop there will be also poster sessions that are only available to registered participants. The list of the papers can be found below (thanks to people who attend it). • A geometric deep learning model to filter out anatomically non plausible fibers from tractograms [video] • Patient-Specific Pathological Gait Modelling with Conditional-NRI [video] • GRASP: Graph Alignment through Spectral Signatures • Isomorphism Leakage in Multi-Interaction Datasets [video] • Integrating Spectral and Spatial Domain Graph Neural Networks • Unshackling Bisimulation with Graph Neural Networks • State2vec: Learning Off-Policy State Representations [video] • Are Graph Convolutional Networks Fully Exploiting Graph Structure? [video] • Principal Neighbourhood Aggregation Networks [video] • Attentive Group Equivariant Convolutional Networks [video] • SMP: An Equivariant Message Passing Scheme for Learning Graph Structural Information [video] • Evaluation of Molecular Fingerprints for Similarity-based Virtual Screening generated through Graph Convolution Networks [video] • Network alignment with GNN [video] • Learning Generative Models across Incomparable Spaces • Learning Set Operations for Deformable Shapes [video] • Instant recovery of shape from spectrum via latent space connections [video] • SIGN: Scalable Inception Graph Neural Networks [video] • Universal Invariant and Equivariant Graph Neural Networks [video] • Graph Convolutional Gaussian Processes for Link Prediction [video] • Deep Graph Mapper: Seeing Graphs through the Neural Lens [video] • Geoopt: Riemannian Optimization in PyTorch [video] • HyperLearn: A Distributed Approach for Representation Learning in Datasets With Many Modalities • Multi-relational Poincaré Graph Embeddings [video] • On Understanding Knowledge Graph Representation [video] • Learning Object-Object Relations in Video [video]